Virtual electrode placement for localization

Abstract

Systems and methods for virtual electrode placement for electrode localization are provided. In one example, a virtual placement system includes a memory for storing instructions and a processor for executing the instructions as operations. The operations include virtually placing a virtual layout of virtual electrodes on a body surface geometry of a patient. The virtual electrodes represent respective physical electrodes arranged on the patient. The operations also include localizing the physical electrodes in three- dimensional space based on the virtual layout of the virtual electrodes.

Description

VIRTUAL ELECTRODE PLACEMENT FOR LOCALIZATION

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 575,932, filed April 8, 2024, the entire content of which is incorporated herein by reference.FIELD

[0002] This description relates to virtual electrode localization, such as to localize and identify individual physical electrodes arranged on a patient’s body.BACKGROUND

[0003] Electrodes are often utilized to measure the physiological functions of the body. One example is electrocardiogram (ECG), which are used extensively in healthcare facilities as well as consumer wearable devices. Knowing the anatomical locations of the electrodes can further enrich the electrical information recorded by the electrodes. As an example, electrode locations have been utilized to obtain electrocardiogram imaging (ECGI), which allows not only diagnosis of the type of cardiac electrical dysfunction but also pointing out the anatomical location(s) of the potential culprit. This can benefit clinical interventions such as cardiac ablation. Traditionally, the locations of the electrodes are obtained through a CT scan of a patient wearing the electrodes or an MRI scan of a patient wearing MRI- compatible fiducial markers (as a surrogate for the electrode location). The need to wear the electrodes or fiducial markers during CT / MRI scans complicates the logistics of workflow and can introduce errors in some cases.SUMMARY

[0004] This disclosure relates to virtual electrode placement, such as to (1) guide electrode placement on a patient’s body surface and / or (2) to facilitate the localization and identification of physical electrodes on the patient’s body surface.

[0005] A first example relates to a system that includes a memory and processor core. The memory can store machine-readable instructions, and the processor core can access the machine-readable instructions and execute the machine-readable instructions as operations. The operations can include generating virtual electrode template data based on virtualelectrode layout data and body surface geometry data, wherein the body surface geometry data represents a three-dimensional surface of a patient’s body surface where physical electrodes are placed or being placed. The virtual electrode layout data represents an identity and a virtual layout of physical electrodes placed on or being placed on the patient. The virtual electrode template data represents the identity and the virtual layout of the virtual electrodes placed on the body surface geometry. The operations further can include determining physical electrode geometry data to localize and identify each of the physical electrodes in three-dimensional space on the body surface based on the virtual electrode template data.

[0006] A second example relates to a computer-implemented method for electrode localization. The method can include generating virtual electrode template data based on virtual electrode layout data and body surface geometry data. The body surface geometry data represents a three-dimensional surface of a patient’s body surface where physical electrodes are placed or being placed. The virtual electrode layout data represents an identity and a virtual layout of physical electrodes placed on or being placed on the patient. The virtual electrode template data represents the identity and the virtual layout of the virtual electrodes placed on the body surface geometry. The method can also include determining physical electrode geometry data to localize and identify each of the physical electrodes in three-dimensional space on the body surface based on the virtual electrode template data.

[0007] A further example relates to one or more non-transitory machine readable media having instructions, which when executed by one or more processors, are programmed to perform the method.

[0008] The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques described in this disclosure will be apparent from the description and drawings, and from the claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] FIG. 1 illustrates an example of a localization engine for a virtual placement system.

[0010] FIG. 2 illustrates an example of digital virtual electrode layout being overlayed into the flattened body surface geometry.

[0011] FIG. 3 illustrates an example of a system that includes a projector to facilitate placement of electrodes onto the body surface of the patient.

[0012] FIG. 4A illustrates an example graphical user interface representing a fused body model of the physical electrodes on body surface geometry.

[0013] FIG. 4B illustrates an example of a set of virtual electrodes having anchor points at virtual electrode locations.

[0014] FIG. 4C illustrates an example of a set of virtual electrodes having adjusted virtual electrode locations.

[0015] FIG. 4D illustrates an example of an electrode vest having anchor points at virtual electrode locations.

[0016] FIG. 5 illustrates an example of an electrode vest for recording electrical signals being worn during imaging of the patient.

[0017] FIG. 6 illustrates an example of a system and components for use in generating electrode geometry data when a patient is wearing electrodes or fiducial markings during medical imaging.

[0018] FIG. 7 illustrates an example system environment that can be used in a workflow to acquire electrophysiological information from a patient.

[0019] FIG. 8 illustrates a flowchart of an example method for a virtual placement method for electrode localization.

[0020] FIG. 9 illustrates an example of body surface geometry of a patient’s body surface as a body surface model of the patient.

[0021] FIG. 10 illustrates an example model of the body surface geometry with a layout of virtual electrodes.

[0022] FIG. 11 illustrates an example of an electrode pairing based on at least one anchor point.

[0023] FIG. 12 illustrates an example of a visual indicator to indicate the measure of quality for mapping of virtual electrode locations with physical electrode locations.

[0024] FIG. 13 illustrates an example of a system that can be utilized for performing medical mapping and / or treatment of a patient.DETAILED DESCRIPTION

[0025] This disclosure relates to virtual electrode placement for localizing physical electrodes on a patient’s body surface, such as to guide placement of real electrodes on the body surface or to facilitate the localization of physical electrodes currently positioned on the patient’s body surface.

[0026] As an example, systems and methods described herein can be used to determine a body surface geometry of a patient’s body surface representing a digitally reconstructed torso / body surface based on physiological data derived from a medical imaging scan of the patient (e.g., using CT or MRI). A digital layout of an electrode array can be accessed (e.g., imported) from memory, which can store digital layouts for a plurality of different electrode arrays, which can be include different sizes having different spatial distributions of electrodes and / or different numbers of electrodes (e.g., one or more electrode panels or other electrode arrangements). As an example, a digital virtual electrode layout describes the physical locations and distribution of the electrodes, including distances between electrodes, in two-dimensional or three-dimensional space. As described herein, the digital virtual electrode layout can vary according to a known electrode array that is placed on or being placed on the patient’s body, and there could be layouts that share similar distribution of electrodes but different sizes. The correct physical dimension of this virtual layout is useful in allowing the ease of guiding or matching the physical electrode layout on the patient’s body in the real world. The systems and methods can execute instructions to place the virtual layout of electrodes onto the body surface geometry.

[0027] One example use scenario for the virtually placed electrodes on a reconstructed body surface is to guide the placement of the physical electrodes on the real body of the same subject. This could be done via approximation or via projection of virtual layout to the subject’s body surface to guide the placement.

[0028] In an example scenario when the physical electrodes are placed on the patient’s body without the guidance of virtual electrodes, the virtual electrodes positions are first placed in typical (or estimated) locations and then adjusted to match the placement of the real electrodes with increased accuracy. In this example use scenario, the virtual layout of electrodes are used to localize the physical electrodes that have been placed on the patient’s body surface. This is achieved by identifying locations of at least three physical electrodes or other spatial locations having a known spatial relationship with the electrodes, anchoringthe corresponding virtual electrodes to those identified locations, and then using the resultant virtual electrode placement of the entire electrode array to ascertain the locations of remaining electrodes in the array.

[0029] Yet another example use scenario for the virtually placed electrodes is to label the electrodes (or other fiducial markers) that are visible from the CT / MRI scan. This can be achieved via automated registration between the virtual electrode positions and the physical electrode / marker positions derived from imaging scans. Once registration and pairing is completed between corresponding virtual and physical marker / electrode locations, unique identifiers for each of the virtual electrodes (e.g., electrode on the left arm, ground electrode, electrode #XX from an electrode array, etc.) can then be assigned to the respective physical electrodes on the patient’s body. As described herein, virtual electrodes thus can be leveraged in a variety of use scenarios to ascertain geometry data that accurately localizes and identifies each of the electrodes placed on the patient’s body.

[0030] The systems and methods described herein can utilize virtual electrodes for localization and identification of physical electrodes on the body surface according to a variety of use scenarios. The systems and methods described herein thus can improve the cumbersome workflow of requiring the patients to have those electrodes or fiducial markers on the body surface during an imaging scan.

[0031] FIG. 1 illustrates an example of a localization engine 100 for a virtual placement system. The localization engine 100 includes machine-readable instructions (also referred to as code), which are stored in memory and executable by a processor. The localization engine 100 includes a geometry calculator 102, a virtual electrode placement function 108, and a physical electrode placement function 110. While FIG. 1 is depicted and discussed with the localization engine 100 as including a discrete section of code 102, 108, and 110 to facilitate discussion of aspects of this disclosure, it is to be understood that in other examples the geometry calculator 102, virtual electrode placement function 108, and physical electrode placement function 110 may have overlapping code / logic (e.g., where one or more of the geometry calculator 102, virtual electrode placement function 108 and / or physical electrode placement function 110 are a module of one another). Similarly, unless specifically discussed otherwise herein, it is to be understood that one of ordinary skill in the art would understand that some or all of each individual portion of code as discussed herein (e.g., localization engine 100, geometry calculator 102, virtual electrode placementfunction 108, and physical electrode placement function 110) may be integrated into and / or overlap with any other individual portion of code as aspects of this disclosure are reduced to practice.

[0032] When executing the geometry generator 102 to the processor will generate body surface geometry data 106 based on image data. The image data 104 can represent physiological data from one or more imaging devices implementing a medical imaging modality. The image data thus can provide three-dimensional image data representing the patient’s torso and / or other region(s) of interest within the patient’s body (e.g., the heart and / or other internal anatomy). The geometry generator 102 can perform image processing functions, such as including extraction and segmentation, to provide segmented image data to identify the body surface and respective surfaces of other regions of interest within the patient’s body (e.g., cardiac surfaces). The body surface geometry data 106 can be automatically created by the geometry generator 102 using manual- or auto-segmentation of the CT or MRI scans of the subject.

[0033] As an example, the auto-segmentation can be effectively achieved using a three- dimensional (3D) U-NET machine learning architecture. For example, segmented image data can be converted into a two-dimensional (2D) and / or 3D graphical representation that includes the volume of interest for the patient. As described, in some examples the image data 104 can be acquired while an array of physical electrodes are on the patient’s body or in the absence of physical electrodes on the body surface. If the physical electrodes are on the body during imaging, the geometry data can also specify locations for each of the body surface electrodes. The body surface geometry data can include a three-dimensional body surface model (e.g., a mesh or other form) representing a portion of the patient’s body surface and one or more surfaces of interest within the patient’s body.

[0034] The electrode array can correspond to a high-density arrangement of body surface electrodes (e.g., greater than approximately one hundred electrodes, greater than approximately two hundred electrodes, two hundred fifty-two electrodes) on one or more panels configured distribute the electrodes over a portion of the patient’s torso (e.g., thorax) for measuring electrical activity associated with the patient’s heart (e.g., as part of an electrocardiographic mapping procedure). Examples of a high-density body surface non- invasive apparatus that can be used as the sensor array are shown and described in the aboveincorporated U.S. Patent No. 9,655,561 and International Publication No.WO 2010 / 054352. Other arrangements and numbers of sensing electrodes can be used as the sensor array. For example, the array can be a reduced set of electrodes on one or more panels, which do not cover the patient’s entire torso and is designed for measuring electrical activity for a particular purpose (e.g., an array of electrodes specially designed for analyzing atrial fibrillation and / or ventricular fibrillation) and / or for monitoring a predetermined spatial region of the heart. In other examples, an array having a traditional or modified 12- lead ECG or a single electrode can be implemented as the sensor array to measure body surface electrical signals.

[0035] Executing the virtual electrode placement function 108 will cause the processor to virtually place a virtual layout of virtual electrodes on the body surface geometry of the patient based on the body surface geometry data 106 and predetermined virtual electrode data 109. The virtual electrode data 109 represents a corresponding virtual spatial location and identity for each of a plurality of physical electrodes or one or more electrode arrays arranged on the patient body surface. The virtual electrode data 109 thus can be selected (automatically or responsive to a user input) to match the physical electrode array that is placed on the patient’s body. For example, a user can select a size of a panel or vest containing the electrode array being used, such as from a drop-down menu. Also, or as an alternative, a model number for the physical electrode array can be selected. In yet another example, a barcode or QR code can be scanned on the physical electrode array, which code can be used to specify and select the virtual electrode data 109. The virtual electrode data can be selected in other ways.

[0036] The virtual layout of electrodes provided by the virtual electrode data 109 can be a 2D representation of the virtual electrodes, which includes a location and unique identifier for each virtual electrode. In an example, the virtual electrode data 109 can represent a virtual layout for front and back virtual panels of virtual electrodes that are to be applied to 3D body surface geometry. In other examples, the electrodes can be represented in other form factors (e.g., one or more panels) or as individual separate electrodes.

[0037] Executing the virtual electrode placement function 108 will cause the processor to place a layout of virtual electrodes on a body surface geometry of a patient. As shown in FIG. 1, when executing the virtual electrode placement function 108 to the processor will generate virtual electrode template data based on the body surface geometry data 106 and virtual electrode data 109. The virtual electrode template data represents the identity (e.g.,a unique ID) and the virtual layout (3D spatial locations) of the virtual electrodes placed on the body surface geometry. Further, executing the physical electrode localization function 110 can cause the processor to identify and localize the physical electrodes in three- dimensional space and provide electrode geometry data 112 based on the virtual electrode template data. As described herein, different example embodiments of the virtual placement function 108 and / or the physical electrode localization function 110 can be implemented depending on a given use scenario. In some examples, the electrode geometry data can be combined with some or all of the body surface geometry data 106 and stored as geometry data representing electrode locations as well as the surface of one or more other regions of interest.

[0038] As an example and with reference to FIG. 2, the virtual electrode data 109 represents the identity and a 2Dvirtual layout of the virtual electrodes, such as a flattened 2D surface representation for the physical electrodes, shown at 200. The body surface geometry data 106 can include a 3D representation of body surface geometry, which can be derived from one or more imaging scans using a 3D imaging modality, such as described herein. Executing the virtual electrode placement function 108 can cause the processor to flatten the body surface geometry data 106 representing the 3D surface of the patient’s body surface to a two-dimensional surface representing the patient’s body surface, shown at 202. In some examples, the body surface geometry with 3D vertices are first split into a number of respective parts (or regions), such as a front part and the back part, and the respective parts can be processed separately. Each of the parts can correspond to a set of physical electrodes, such as can be, such as corresponding to a multi-part electrode array implemented on respective panels shown and described in U.S. Pat. No. 9,655,561. Other arrangement of electrodes can be used in other examples.

[0039] In some examples, the virtual electrode placement function 108 can use multidimensional scaling to transform vertices from 3D coordinates of body surface geometry data 106 to respective 2D coordinates, such as implemented in a way that preserves inter-point distances (as much as possible). The virtual electrode placement function 108 can then apply (e.g., spatially map) the 2D layout of the virtual electrodes 200 to the two-dimensional surface of the patient’s body surface 202 to provide a two- dimensional virtual placement of the virtual electrodes, such as shown in FIG. 2 for part of the virtual electrodes (e.g., a panel representing a portion of the virtual electrodes). The 2Dlayout of the virtual electrodes can be applied to the flattened 2D surface by assigning each of the virtual electrodes in the 2D virtual layout to respective spatial coordinates on the 2D surface of the patient’s body surface to provide 2D virtual placement data representing the identity and 2D location of the virtual electrodes (e.g., in a 2D coordinate system). In examples when the virtual electrodes are separated into respective parts, each part of the two-dimensional layout of the virtual electrodes 200 can be applied to the corresponding two-dimensional surface of the patient’s body surface in a similar manner.

[0040] Executing the virtual electrode placement function 108 further can cause the processor to transform the 2D virtual placement of the virtual electrodes into a 3D virtual placement, corresponding to the virtual electrode template data, based on the two- dimensional virtual placement data and the body surface geometry data. Thus, the virtual electrode template data thus represents the identity and virtual placement of the virtual electrodes on the 3D surface of the patient’s body surface. Executing the physical electrode localization function 110 causes the processor to determine physical electrode geometry data 112 to localize and identify each of the physical electrodes in three-dimensional space on the body surface based on the virtual electrode template data (e.g., provided by the virtual electrode placement function 108). In some examples, the 2D virtual electrodes (defined by the virtual electrode data 109) can be mapped onto the 3D body surface geometry (e.g., a 3D model of the body surface described by the body surface geometry data 106) by interpolating functions, which are created based on the 2D and 3D coordinates of mesh nodes in the body surface geometry data 106.

[0041] The physical electrode localization function 110 can be used to guide the placement and alignment of physical electrodes on the patient’s body and to enable the physical electrode localization function 110 to accurately determine the electrode geometry data 112. Because the virtual electrode array has the same dimension and distribution of physical electrodes and the virtual electrodes are virtually placed on the same patient at respective locations where the real electrodes are to be applied, the localization function 110 can provide an accurate estimate of the physical electrode placement for each of the respective physical electrodes. This further allows testing of different electrode vest layout and sizing before physically placing the vest as well as experimenting and finding the optimal electrode placement strategy in the virtual environment.

[0042] As an example, the physical electrode localization function 110 can provide a graphical representation of the virtual electrode placement based on the virtual electrode template data. The graphical representation of the virtual electrode placement can be displayed in a screen, such as a visual display, an augmented reality device, a projected visualization, or the like. The displayed graphical representation of the virtual electrode placement provides a visual guidance that provides an objective indication of accuracy when placing the real electrode array (e.g., vest or panel of electrodes) on a given patient.

[0043] As a further example, FIG. 3 illustrates a system 300 that includes the localization engine 100 and a projection system 302. In an example, the localization system is configured to provide guidance image data to the projection mapping system 302, such as through a wireless or physical connection. Also, or alternatively, the guidance image data can be stored in a portable storage device (e.g., flash memory device), which can be attached to a corresponding interface port of the projection system 302 to provide the guidance image data accessible to the projection system. The projection system 302 includes an image projector. In some examples, the projection system 302 is a 3D projection mapping system that includes an image projector and a camera.

[0044] In the example of FIG. 3, the localization engine 100 is shown as an example embodiment of the physical electrode localization function 110, which includes a guidance generator 306, a projection image generator 308, a feedback / image processor 310 and a graphical user interface (GUI) 312. It is understood that the localization engine 100 can include other functions, such as described with respect to FIG. 1. Also, or as an alternative example, the functionality of the guidance generator and / or GUI can be implemented as part of the projection system 302.

[0045] Executing the guidance generator 306 causes the processor to provide guidance to facilitate placement of the physical electrodes on the patient’s actual body surface. As shown in the example of FIG. 3, the guidance generator 306 includes projection image generator 308 that is configured to provide projection image data describing a graphical representation of the virtual electrode layout (e.g., an electrode layout image in a suitable image file format) based on the virtual electrode template data. As described herein, the virtual electrode template data, which is generated by the virtual electrode placement function 108, represents the identity and the virtual layout of the virtual electrodes placed on a representation of the body surface geometry.

[0046] The projection system 302 includes a projector configured to project a projected image 314 onto the patient’s body 316 based on the virtual electrode template data. In some examples, the camera of the system 302 acquires an image of a patient 316 and provides corresponding image data of the patient to the localization engine 100. Executing feedback / image processor 310 can cause the processor to adjust the projected image based on the image of the patient acquired by the camera. The GUI 312 can be used to control the projection system 302 responsive to a user input instruction, such as to adjust the projected image, including scaling, distribution and / or brightness of the projected image 314. The GUI 312 can also include a GUI element (e.g., a radio button or other control) that can cause the processor to control the physical electrode localization function 110 responsive to a user input to confirm that the physical electrodes have been placed at desired locations based on the guidance provided by the projected image 314. The user inputs can be provided via one or more user input devices (e.g., keyboard, mouse, touchscreen, gesture control, or the like) that is coupled to the computing apparatus implementing the localization engine 100.

[0047] As a further example, the camera of the projection system 302 can be configured to control scaling and distribution of the projected image based on the image acquired by the camera. Also, or as an alternative, the localization engine 100 and the feedback / image processor 310 adapt the projector image data based on the 3D topography of the patient’s body to enable projection of the image 302 across the patient’s 3D body surface to accurately reflect respective electrode locations based on the virtual electrode template data. Also, or as an alternative to the camera, the topography of the body surface of the patient 304 where the electrodes are being placed can be determined by other devices than the camera, such as laser scanner, a digitizer, LiDAR or the like. The feedback / image processor 310 may adjust scaling and distribution of the projected image based on the image data 104 acquired by the camera of the projection system 302 and / or based on spatial information about the topography acquired by such one or more other devices.

[0048] As described herein, the projection image generator 308 of the guidance generator 306 can generate the projected image 314 based on the virtual electrode template data and / or other information to provide guidance to a user to place one or more designated parts and / or the entire panel(s) at particular locations on the patient’s body 316. In some examples, the projected image 314 can include an outline for all or a portion of an electrode vest or panel, such as shown in FIG. 3 for a left panel. In other examples, the projectedimage 314 could provide guidance in other forms, such as by projecting an arrangement of a set of specific electrode at designated locations on the body surface, individual virtual electrodes, a set of fiducial marks, etc. The projected image thus provides a direct visual guide on where to place the electrode array (or individual electrodes) and eliminate the potential errors of “eye-balling”. Because the physical electrodes are placed on the body surface at locations specified by the projected image, each of the physical electrodes match the locations of the virtual electrodes (as provided in the virtual electrode template data). As a result, the physical electrode localization function 110 can determine the electrode geometry data 112 for the physical electrodes to be the same (or substantially the same) as the virtual electrode template data as generated by the virtual electrode placement function 108. Similar guidance images can be generated and projected on the patient’s body for each of the body surface locations where electrodes are to be placed, and a user can place respective physical electrodes according to the projected images. After all requisite electrodes have been placed and the electrode geometry data 112 has been determined for such electrodes, as described herein, the identity and locations of the physical electrodes provided by such data 112 can be integrated with the electrical data recorded from the electrodes to provide advanced functional imaging, such as ECGI.

[0049] As another example, alignment between virtual locations physical electrodes can be determined based on one or more anchor points. The anchor points can be used for determining the electrode geometry data for example embodiments in which the body surface geometry data 106 is derived based on one or more image scans acquired without the physical electrodes placed on the patient’s body surface. That is, the body surface geometry data 106 does not include locations for the physical electrodes that are placed or being placed on the patient’s body. The anchor points provide a mapping (or association) between a virtual location (e.g., spatial coordinates from the virtual electrode template data) and a respective physical location of a physical electrode (e.g., spatial coordinates from the physical electrode geometry data). In an example, the anchor points may be electrodes with known physical locations on the body surface geometry. In other examples, different points or structures having known physical locations relative to the electrodes on the body surface can be used as anchoring points, such as anatomical landmarks or other fiducial markings. As described herein, the anchor points can be defined by a user eye-balling the locations oflandmarks according to the location of physical electrodes on the patient’s physical body and / or through the use of cameras.

[0050] As described herein, the physical electrode array may include an arrangement of electrodes on one or more pliable panels that are able to maintain the electrode distribution with reasonably coherent stretchability. The localization engine 100 can thus anchor / pin corresponding virtual electrodes to the known locations on the body surface geometry through a GUI (e.g., the GUI 312). The physical electrode localization function 110 causes the processor to determine the positions of the remaining electrodes in 3D space based on the anchor points that have been selected. The physical electrode localization function 110 can cause the processor to determine the positions and identity of the remaining physical electrodes based on the anchor points and based on an assumption that the distribution of the electrodes is relatively constant.

[0051] As an example, at least three anchor points can be identified in response to a user input on a GUI (e.g., the GUI 312) that includes an interactive graphical representation of the physical electrodes on graphical representation of a body. Other numbers of anchor points can be used in other examples, and an increased number of anchor points is expected to increase the accuracy in localizing the remaining electrodes. For example, a user can use a mouse or other user input device to move a pointing device to a given anchor point on the interactive GUI and ‘click on’ or otherwise select the anchor point location to specify each of the respective anchor points based on where each respective anchor point is actually located on the patient’s body. The interactive GUI can display a graphical representation of the virtual layout on the patient’s body surface based on the virtual electrode template data. The three or more anchor points can be selected in response to a user input specifying correspondence between locations represented in the virtual electrode template data and respective locations of the physical electrodes on the patient’s body surface (as observed by the user, e.g., by eyeballing each anchor point location). The physical electrode localization function 110 can cause the processor to determine a transformation matrix based on the user input specifying the anchor points. The physical electrode localization function 110 further can cause the processor to apply the transformation matrix to the virtual electrode template data to localize and identify each of the physical electrodes in a three-dimensional coordinate system and provide the physical electrode geometry data 112.

[0052] As a further example, choice and positions of the anchoring points can be provided to the localization engine 100 as manual user input at a user input device through an anchor point GUI. For example, if electrode number “72” is located at 5 cm above the belly button, the user can simply click that location on the body surface geometry and provide the electrode number “72.”

[0053] As yet another example, the system 100 can include a camera adapted to provide camera image data representing an image of the physical electrodes placed on the patient’s body surface. The camera image data is representative of the electrodes placed on the body surface, which can be textured mapped to the body surface geometry based on an estimated camera model to provide a fused body model, which can be displayed as part of an interactive GUI (e.g., the GUI 312). The estimated camera model can enable a processor executing code to cause a photo of the patient body wearing the electrode array to be projected onto the 3D body surface geometry. The anchor points thus can be manually selected from the interactive GUI in response to a user input instruction selecting respective anchor points on the GUI. In some examples, as shown in FIG. 4A, a GUI 400 can be generated to represent the fused body model of the physical electrodes on body surface geometry. A user can simply move a pointer 402 using a user input device to select (or click) an electrode 404 on the body surface geometry that is being displayed in the GUI 400 with a virtual electrode layout and then enter a respective electrode number (e.g., in a dialog box or drop down list) to assign an identity to each selected electrode. Also, or as an alternative, the identification of the selected electrode can be performed automatically via computer vision. Other landmarks or indicia can also be selected as anchor points in other examples.

[0054] By way of further example, FIGS. 4B and 4C demonstrate the use of anchor points to compute a transformation that is applied to the virtual electrode template to determine electrode geometry data 112. For purposes of simplification of explanation, the example of FIGS. 4B and 4C shows 17 electrodes in a triangular arrangement; however, any shape and number of electrodes can be used. The virtual layout 410-1 of FIG. 4B includes a first anchor point 412-1, a second anchor point 414- 1 , and a third anchor point 416- 1. The anchor points 412-1, 414-1, and 416-1 can be selected according to the approaches described herein (e.g., eyeball or using a camera to map the camera image of the physical electrodes to the virtual electrode template. The transformation matrix can be generated to localize thephysical electrodes based on at least three anchor points identified in the virtual layout 410- 1 or the body surface geometry of the patient. The transformation matrix indicates stretching, rotating, angling, etc. the virtual layout 410-1 to the virtual layout 410-2 including the first anchor point 412-2, the second anchor point 414-2, and the third anchor point 416-2 at different virtual positions, such as shown in FIG. 4C.

[0055] As a further example, the electrode arrangements may be based on a specific configuration of physical electrode vest, which can be a continuous vest or include multiple parts (e.g., panels) such as described herein. In such an example, a 2D virtual electrode layout is placed on the 3D body surface in their typical locations to provide a 3D virtual layout, such based on virtual electrode template data generated by the virtual electrode placement function 108. FIG. 4D illustrates a GUI 450 that includes a virtual layout of electrodes (e.g., a vest) 452 in 3D space on a 3D body surface 454 (e.g., based on the body surface geometry data 106). The GUI 450-1 includes a set of virtual anchor points shown at 462-1, 464-1 and 466-1 that have been identified at their typical spatial locations based on the virtual electrode template data. The GUI 450-1 also includes another set of physical anchor points 462-2, 464-2 and 466-2 representative of the true physical locations for each of the identified virtual anchor 462-1, 464-1 and 466-1. As described herein, the physical anchor points 462-2, 464-2 and 466-2 can be provided in response to a user selecting (e.g., clicking with a pointer) the true location of each of the anchor points (e.g., electrodes or landmark) in the GUI 450 based on observing the location of each anchor point according to the placement of physical vest on the patient’s body. As a result, each of the anchoring points has a respective pair of positions (e.g., paired 3D spatial coordinates), in which one position represents coordinates in the virtual 3D layout, shown on the GUI at 462-1, 464-1 and 466-1, and the other position represents an actual position of physical electrode responsive to the user specifying a true location on the patient’s body, shown on the GUI at 462-2, 464-2 and 466-2.

[0056] The physical electrode localization function 110 includes code that causes the processor to generate a transformation matrix based on the paired positions of the three or more anchor points identified on the GUI 450. The transformation matrix indicates an amount of stretching, rotating, angling, etc. for locations of electrodes in the 3D virtual layout 452 of FIG. 4D to shift the electrode locations according to their true locations shown at 462-2, 464-2 and 466-2. The resulting electrode geometry data 112 thus includes adjustedlocations for each electrode location in the virtual layout based on the transformation, such as the similar to the transformation shown with respect to the simplified example of FIG. 4C, in which each of the anchor points and respective electrode locations have been adjusted based on the transformation matrix. The electrode geometry data 112 thus can include the identity and 3D locations of the physical electrodes and the data 112 can be integrated with the electrical data recorded from the physical electrodes to implement ECGI or other imaging techniques.

[0057] It has been discussed that this virtual electrode placement can eliminate the need for the patient to wear the electrode during medical imaging (e.g., CT or MRI scan). However, the virtual electrode placement can still be useful in a workflow where the patient wears the electrode array during CT scan or fiducial markers during MRI scan. Turning to FIG. 5, when the locations of the electrode or fiducial markers can be easily detected due to higher image intensity in CT and MRI scan 500, those electrodes may be localized. For example, a particular electrode, such as a first electrode 502, and then associate that location with the electrical signals from the first electrode 502. This can be done manually for each electrode but it tends be a tedious process if there are many electrodes in the electrode array. The virtual electrode placement function 108 can be used to automate this process. This may be done via registration between the detected electrode locations from CT / MRI scans with the virtual electrodes placed on the same patient in the typical locations. The registration could be successfully performed using coherent point drift (CPD), a typical non- rigid registration method that maintains the topological structure of the point clouds during the alignment process.

[0058] FIG. 6 illustrates an example of a system 550 that includes an example embodiment of the localization engine 100 which can be executed to cause a processor to determine the electrode geometry data 112 for a scenario when the physical electrodes are placed on the patient’s body during a medical imaging scan that produces the image data 104. Thus, the one or more images provided in the image data 104 include the physical electrodes on the patient’s body surface. Also, or as an alternative, the one or more images can include fiducial markers, which are compatible with MRI and placed on the body during imaging by the imaging modality would be incompatible with the physical electrodes. Such fiducial markers can be placed on the body at some or all locations where physical electrodes are to be placed on the patient’s body surface and / or locations having a known spatialposition relative to the physical electrodes that are to be placed on the patient’s body. The body surface geometry data 106 can include 3D spatial locations of the spatial locations of the physical electrodes on the patient’s body surface or the spatial locations of the physical electrodes on the patient’s body surface can be derived from the body surface geometry data 106, as described herein.

[0059] In the example of FIG. 6, the localization engine 100 includes a point cloud generator 552. The point cloud generator 552 causes the processor to generate a first point cloud data representing spatial locations of the virtual electrodes in a first point cloud. In some examples, the virtual electrode placement function 108 can include (or invoke) an instance of the point cloud generator 552 to generate the virtual electrode template data to include the 3D locations of the virtual electrodes represented as respective points in a virtual electrode point cloud. The virtual electrode template data also includes data describing the identity (e.g., a unique ID) for each virtual electrode represented in the virtual electrode point cloud.

[0060] The spatial locations of the physical electrodes, as provided in the body surface geometry data can also be represented as a second point cloud. For example, the geometry calculator 102 or another function of the localization engine 100 can include or invoke an instance of the point cloud generator 552 to generate the point cloud representation describing the 3D spatial locations (e.g., 3D coordinates) for the physical electrodes. In an example, the point cloud generator 552 can cause the processor to generate the point cloud representation for the physical electrodes based on the body surface geometry data 106. In another example, the point cloud generator 552 causes the processor to generate the point cloud representation for the physical electrodes based on the image data 104 acquired by at least one imaging scan of the patient’s body with the respective physical electrodes and / or fiducial markers placed on the patient’s body surface. Data for the virtual electrode point cloud and the physical electrode point cloud can be stored in memory.

[0061] As a further example, the physical electrode localization function 110 will cause the processor to generate the physical electrode geometry data 112 based on the virtual electrode point cloud and the physical electrode point cloud. In the example of FIG. 6, the physical electrode localization function 110 includes point cloud registration code 554 that causes the processor to register the virtual electrode point cloud and the physical electrode point cloud. The point cloud registration code 554 can implement a non-rigid registrationmethod to find correspondence between the points in each of the virtual electrode and the physical electrode point clouds. In some examples, the identity of the physical electrodes can be unknown or indeterminable due to variations in actual placement on the body surface. Accordingly, the physical electrode localization function 110 can include ID assignment code 556 that causes the processor to assign an identity for each of the respective physical electrodes based on the correspondence determined by the point cloud registration code 554. For example, the ID assignment code 556 can transfer (or copy) data describing the known identity for each of the virtual electrodes from the virtual electrode template data to the respective physical electrodes. In this way, the determined physical electrode geometry data 112 includes a three-dimensional spatial location and identity for each of the respective physical electrodes.

[0062] FIG. 7 depicts a diagram of an example system environment 600 that can be used in a workflow to acquire electrophysiological information from a patient 602. The patient 602 is a biological entity, such as a human (e.g., an adult, a child) or an animal (e.g., a pet, wildlife). An arrangement of physical electrodes 604 can be placed on the outer surface of the patient’s body, such as on the chest or thorax. The arrangement of physical electrodes 604 may be worn as an electrode vest having a plurality of physical electrodes. Other types or numbers of electrodes can be used in the system 600. The physical electrodes of the arrangement of physical electrodes 604 can sense electrical signals that quantify internal ionic currents or voltages at respective locations on the surface of the patient’s body. The electrical signals sensed by the physical electrodes 604 are received by a monitoring system 606. The monitoring system 606 can include signal processing circuitry (e.g., amplifiers, filters, signal converters and the like) to provide electrophysiological data based on the electrical signal received through respective channels for each of the physical electrodes. The monitoring system 606 can thus sense and determine physiological data of the patient 602 based on the electrical signals received from the physical electrodes. For clarity, examples herein are described in the context of detection and analysis of cardiac electrical signals. However, the systems and methods described herein are equally applicable to other types of physiological signals and related diagnostic techniques. For example, diagnostic techniques for monitoring the brain of the patient may include an EEG utilizing a wearable cap of physical electrodes and an MRI scan of the brain of the patient. The examplesprovided herein are not limited to a specific diagnostic technique, modality, or body part of the patient 602.

[0063] Although described as electrodes, the electrical signals may be received from other medical devices. The medical devices may be wearable devices that include computing device components (e.g., a processor) with circuitry that can be worn or attached to the patient 602. The wearable device communicates physiological data, for example, to the monitoring system 606. In some example embodiments, the wearable device may be a portable device (e.g., a mobile device, a portable medical device).

[0064] The patient 602 may also undergo medical imaging from an imaging device 608 as part of the medical procedure or workflow. Medical imaging refers to any technique and / or process of creating visual representations of anatomy that includes the interior of a body, such as for clinical analysis and medical intervention, as well as visual representation of the function of some organs or tissues (physiology). Medical imaging thus may reveal internal structures hidden by the skin and bones. Some examples of medical imaging include devices configured to implement one or more imaging technologies, such as including X- ray radiography, fluoroscopy, medical ultrasonography or ultrasound, tomography (X-ray computed tomography (CT), positron emission tomography (PET), single-photon emission computed tomography (SPECT), magnetic resonance imaging (MRI) and the like), as well as other imaging techniques. These or other imaging modalities may also be utilized, individually or in combination, in other examples to provide medical imaging data.

[0065] The imaging device 608 thus refers to one or more devices configured to perform medical imaging and may include a CT device, MRI device, ultrasound device, x- ray device, fluoroscope device, ultrasound device, and mammogram device, among others. The physiological data may be received from the imaging device 608 by an imaging system 610 as physiological data related to a corresponding CT scan, MRI scan, ultrasound scan, mammogram, image, and dataset, among others. In addition to the arrangement of physical electrodes 604 and the imaging device 608, the physiological data may be received from one or more sensors, such as bio-monitoring sensors, heart rate sensors, blood pressure sensors, oxygen content sensors, respiratory sensors, perspiration sensors, imaging sensors, pupil dilation, gestures, as well as any other kinds of sensors for monitoring the patient 602.

[0066] The system 600 may also include a camera 612 having a sensing mechanism. The camera 612 may include range-gated time of flight (ToF), radio frequency-modulatedToF, pulsed-light ToF, and projected-light stereo. The camera 612 provides image frames that include images (sometimes in color) and / or depth information for each pixel (depth images). A range imaging device, including light detection and ranging (LiDAR), flash LiDAR, time-of-flight (ToF) camera, and RGB-D camera, among others. Additionally, the camera 612 can include a digital optical camera that is non-depth based and capable of acquiring and reconstructing an image of a three-dimensional object, such as the patient 602, from a range of different camera viewing angles (e.g., a cell phone or other portable handheld device that includes a monoscopic camera). In some examples, the camera 612 can be used to digitize the electrodes positions on the patient’s body 602.

[0067] FIG. 8 illustrates a flowchart of an example method 700 for virtual placement for electrode localization. For simplicity, the method 700 will be described as a sequence of blocks, which can be executed by a processor, but it is understood that the elements of the method 700 can be organized into different architectures, elements, stages, and / or processes. For purposes of simplification and by way of illustration, FIGS. 9-12 are used to explain various parts of the method 700, and the same reference numbers in FIGS. 9-12 refer to the same structure. Additionally, the method 700 can be implemented as part of a processor executing the machine-readable instructions described with respect to examples of FIGS. 1-6. Accordingly, aspects of the description of FIG. 8 may also refer to FIGS. 1- 6.

[0068] At block 702, the method 700 includes determining (e.g., by the geometry generator 102 of FIG. 1) a geometry of a body surface of the patient 602 based on physiological data from a medical imaging scan of the patient 602. Turning to FIGS. 6 and 9, the body surface geometry 800 represents a three-dimensional (3D) body surface model representing the shape of at least a portion of the body surface of the patient 602. For example, the body surface geometry 800 may represent the torso (e.g., thorax) of the patient 602. The body surface geometry 800 may be a single volume mesh and / or a point cloud representative of the surface of the body of the patient 602.

[0069] As an example, the geometry generator 102 receives image data (e.g., image data 104) from an imaging system 610 for a medical imaging scan, which may be a CT scan or MRI scan acquired by an imaging device 608. The imaging device 608 may be moved around the patient 602 to capture a set of image frames of the different portions within its field of view of the torso surface, which collectively provide a three-dimensional image datarepresenting the patient’s torso and / or other region(s) of interest within the patient’s body. The imaging device 608 can also be configured to perform image processing on the three- dimensional image data, such as including extraction and segmentation to provide segmented image data to identify the body surface and respective surfaces of other regions of interest (e.g., cardiac surfaces). For example, segmented image data can be converted into a two-dimensional or three-dimensional graphical representation that includes the volume of interest for the patient. As described, in some examples the image scan can be acquired while the physical electrodes are on the patient’s body or in the absence of physical electrodes on the body surface.

[0070] For example, the geometry generator 102 may construct the body surface geometry 800 shown in FIG. 9 based on the segmented image data derived from the set of one or more 3D images provided in the image data 104. Alternatively, the image data may be received from a medical database. For example, the physiological data may be captured from pre-existing medical images of the patient 602. Thus, the geometry generator 102 may be executed by a processor to construct the body surface geometry 800 from the previously acquired images.

[0071] In some example embodiments, the body surface geometry 800 includes locations representative of physical electrodes on the body surface geometry. For example, the model represented by the body surface geometry 800 can be fused with an image of the patient 602 wearing an arrangement of physical electrodes 604 to generate a fused body model, such as the fused model 400 shown in FIG. 4. Thus, the fused body model 400 can include the 3D body surface model of the patient's torso and a representation of physical electrodes distributed across the patient's torso. The physical electrodes can be identified based on an image from a camera (e.g., camera 612) or the medical imaging scan, for example, based on image processing of acquired images described herein. Additionally or alternatively, text or other markers visible to another imaging device may be printed on the physical electrodes that are recognizable via image processing (e.g., using optical character recognition) or in response to a user input. In other examples, the location of the physical electrodes 604 can be acquired by a digitizer, manual measurements or other non-imaging based technique.

[0072] Returning to FIG. 8, at block 704, the method 700 includes virtually placing a virtual layout of virtual electrodes on the body surface geometry of a patient (e.g., by theprocessor executing the virtual electrode placement function 108). For example, as shown in FIG. 10, a graphical representation of a body model 900 includes a set of virtual electrodes 902 placed on body surface geometry (e.g., at typical locations) based on virtual electrode template data. As described herein, the virtual electrode template data includes locations of the virtual electrodes and a respective identifier (e.g., a unique ID) for each virtual electrode. The virtual electrodes 902 may include graphical objects, text and / or numerical information, or a combination thereof according to the virtual electrode template data. Any number of representations may be generated for each virtual electrode 902. In some example embodiments, the virtual electrodes 902 may be represented as a point cloud in the spatial domain.

[0073] The set of virtual electrodes 902 can be used to provide a visual representation of medical devices worn or attached to the patient 602. Executing the virtual electrode placement function 108 will cause the processor to distribute virtual electrodes of the set of virtual electrodes 902 across the 3D body surface geometry 800 (e.g., based on virtual electrode data 109 describing a 2D virtual layout and electrode identifiers) . The virtual electrodes of the set of virtual electrodes 900 may be automatically applied to the body surface geometry 800 or be applied to the body surface geometry 800 based on user input from a user, for example, via a user input on a GUI presented on a display.

[0074] The virtual electrodes 902 can be applied to the body surface geometry individually or in one or more defined groups of electrodes. The virtual locations may be determined based on the coordinate system of the body surface geometry 800 and / or the physiological data, such as the size of the patient 602, the portion of the body surface of the patient 602, a diagnostic type, the number, configuration and arrangement of physical electrodes applied to the patient’s physical body, etc. For example, if the physical medical devices are electrodes worn in a physical electrode vest, the virtual electrode placement function 108 may generate the set of virtual electrodes 902 based on a 2D virtual electrode layout or virtual vest template.

[0075] Referring again to the example of FIG. 10, a virtual vest template includes or represents a layout of one or more subsets of the virtual electrodes from the set of virtual electrodes 902. For example, the virtual electrode placement function 108 can cause a processor to generate the set of virtual electrodes 902 by applying the virtual vest template, including a first subset of virtual electrodes 906 (e.g., corresponding to a first front panel ofthe physical electrode vest) and a second subset of virtual electrodes 908 (e.g., corresponding to a second front panel the physical electrode vest) to estimated locations on the body surface geometry 800. There can be any number of one or more vest panels for which respective subsets of virtual electrodes can be provided. The virtual locations of the virtual electrodes may be based on the size (e.g., small, medium, large, etc.) of a selected physical electrode vest. Therefore, the set of virtual electrodes 902 may be generated for the fused body model 900 to represent a corresponding set of physical electrodes 604 worn by the patient 602.

[0076] Returning to FIG. 8, at block 706, the method 700 includes localizing (e.g., by the processor executing the physical electrode localization function 110) the physical electrodes in three-dimensional space based on the virtual layout of the virtual electrodes 902. Adjusting the virtual locations of the set of virtual electrodes 902 can include coherently shifting, rotating, and / or stretching the virtual electrodes of the set of virtual electrodes 604 by a transformation matrix derived from a spatial relationship between virtual and physical positions of anchor points. For example, executing the physical electrode localization function 110 will cause the processor to calculate an adjustment vector of the transformation matrix, having a distance and direction in 3D space as geometry data, to adjust the virtual location of a virtual electrode to correspond to a physical electrode. Adjustment vectors may be calculated for one or more of the virtual electrodes of the set of virtual electrodes 902. Accordingly, the transformation matrix provides a mapping between virtual and physical electrode locations. The adjustment of the virtual locations is based on the type of anchor point.

[0077] Localizing the physical electrodes in three-dimensional space also may include assigning an identifier to a physical medical device corresponding to a virtual electrode of the subset of virtual electrodes based on an adjusted virtual location of the virtual electrode. For example, because the virtual electrodes of the set of virtual electrodes 902 include identification information for the virtual electrodes such that individual virtual electrodes are differentiable, the physical electrode localization function 110 can be executed by the processor to assign identification information from a virtual electrode to a corresponding physical electrode. Therefore, electric signals measured by each of the individual physical electrodes can be differentiated (e.g., tracked) and thus be linked programmatically to a respective electrode input channel based on the identification information.

[0078] As one example, the image data 104 may be stored in the memory or a medical database. The image data 104 includes the fused body model 900 of the patient 602, the adjustment vectors of the mapping between virtual and physical electrode locations, the identifiers assigned to the physical medical devices, etc. The electrode geometry data may include one or more graphical maps demonstrating locations of the physical electrodes with the respective identifier. In some examples, a quality score is calculated to determine the accuracy of the mapping between the virtual and physical electrode locations. For example, the physical electrode localization function 110 may calculate a quality score of the localization of the physical electrodes. A visual indicator may be displayed on a display of the monitoring system 606 to indicate the quality score on the virtual layout based on the quality score (see, e.g., FIG. 12).

[0079] At 708, the method 700 of FIG. 8 can include providing geometry data. As described herein, the geometry data can include 3D locations of physical electrodes and unique identifiers for the respective physical electrodes (e.g., the electrode geometry data 112). In addition to the electrode geometry, the geometry data provided at 708 can include 3D cardiac anatomy, such as data describing one or more cardiac surfaces (e.g., endocardial and / or epicardial surfaces). Alternatively, in other examples, geometry data describing the cardiac anatomy can be stored separately from the electrode geometry.

[0080] As a further example, the method 700 of FIG. 8 can be executed by processor to determine the electrode geometry data in example embodiments when electrodes and / or fiducial markers having known spatial locations for the electrodes are placed on the patient’ s body during imaging. The image data (e.g., image data 104) thus includes images representative of the electrode locations or the electrode locations can be derived from the image data. For example, turning to FIG. 11, respective point clouds for each of physical and virtual electrode locations can be generated (e.g., by the processor executing the point cloud generator 552). The physical electrodes can be localized at 706 by pairing locations between respective virtual and physical point clouds. The pairing between virtual and physical locations of electrodes can be implemented by performing point registration between respective point clouds (e.g., by the processor executing the point cloud registration function 554). As an example, a first physical electrode location 1102 from the fused body model 900 can be paired with a first virtual electrode 1104 from the set of virtual electrodes 902 of the virtual vest template. For example, a pairing between the first physical electrode1102 and the first virtual electrode 1104 can be visualized on a GUI by a graphical link 1106 between physical and virtual electrodes. A similar link 1106 can be visualized for each pairing, such as virtual and physical electrode locations 1108 and 1110. The link between each electrode pairing can be used (e.g., by the processor executing the ID assignment function 556) to transfer an identity from each virtual electrode to the corresponding physical electrode. In some examples, such as where the locations of virtual and physical electrodes differ by a sufficient amount to introduce error when pairing (e.g., wrong electrodes are being paired), as user can modify pairings using the GUI 312 such as by correcting pairings in response to a user input.

[0081] Turning to FIG. 12, a processor execute further instructions to cause an output to be provided to a display that includes graphics and / or an interactive GUI 1200 based on electrode geometry data. The GUI 1200 can visualize physical locations and identifiers 1202 respective physical electrodes on body surface geometry, such as can be derived from image data (e.g., image data 104) and electrode geometry data (e.g., data 112), as described herein. In some examples, an operator may adjust the default locations of one or more virtual electrodes to facilitate pairing between virtual and physical electrodes. For example, adjustments may be received via the GUI 1200 in response to a user input. The GUI 1200 and / or user input device can include one or more input buttons, switches, touch screen, touch pad, pointer, lights, microphones, speakers, and LEDs, among other ways to interact with the GUI.

[0082] In some examples, the physical electrode localization function 110 may ascertain a measure of quality for one or more the electrode pairings. For example, the physical electrode localization function 110 may generate a visual indicator 1204 to indicate the measure of quality for each of the electrode locations or groups of two or more electrode locations. The visual indicator 1204 can be a graphical representation of an expected electrode pattern. The visual indicator 1204 of the expected electrode pattern can be superimposed on the visualization 1200 of the electrodes to provide a quality metric.

[0083] In other example embodiments, the method of FIG. 8 can be executed by the processor to determine the electrode geometry data when electrodes or fiducial markers for electrodes are absent during medical imaging. In such examples when physical electrode locations are not included in image data (e.g., image data 104), the physical electrodes can be localized at 706 by spatially localizing a plurality of (e.g., three or more) anchor pointsbetween virtual and physical electrode locations. As described herein, there are several approaches that can be used to obtain the true physical locations of the anchor points. One approach is eye-balling using landmarks, and another approach is through the use of one or more cameras. If the location(s) of the physical medical device(s) (e.g., one or more electrodes) are unknown, the physical electrode localization function 110 may identify the anchor points as the imaged physical medical device(s) from the camera 612. For example, the processor will execute the physical electrode localization function 110 to identify anchor points as imaged physical medical device(s), such as the physical electrode(s) 604. The locations of the physical medical devices may be unknown. Alternatively, the physical electrode localization function 110 may identify the anchor points based on the image from the camera 612 combined with the medical imaging scan, for example, a set of acquired images, CT scan, MRI scan, etc. from a fused body model.

[0084] As a further example, the body surface geometry 800, the body model 900, and the medical imaging scans may not include location or identify information for the physical electrodes. Accordingly, the anchor points can be identified in the fused body model (e.g., displayed as a GUI) in response to a user input (e.g., to select / click) on a respective location in the GUI for the fused body surface / model. In some examples, the anchor point is anatomically meaningful. As examples, the collar bone, iliac crest, armpits, navel, etc. may each be used as an anchor point. These or other anchor points may be defined manually. The selection of a particular location as an anchor point can define a true physical location. After anchor point locations have been determined in both physical and virtual domains, a transformation is determined. The physical electrode localization function can apply the transformation to the virtual electrode locations to match respective locations of the physical electrodes. Following the transformation or concurrently therewith, the physical electrodes can be identified, such as in response to a user input in which the user enters the electrode identifier (e.g., an electrode ID or label) for some or all physical electrodes. For example, the electrode identifier can be learned from a color / image fused on the 3D body model. In some examples, the physical electrode localization function can use pattern recognition via computer vision and / or machine learning machine-learning based approaches to localize physical electrodes based on anchor points and / or determine the identity of physical electrodes.

[0085] FIG. 13 depicts an example of a system 1450 that can be utilized for performing medical testing (diagnostics, screening and / or monitoring) and / or treatment of a patient. In some examples, the system 1450 can be implemented to generate corresponding maps for a patient’s heart 1452 in real time as part of a diagnostic procedure (e.g., an electrophysiology study) to help assess the electrical activity and identify arrhythmia drivers for the patient’s heart corresponding to connected trajectories. Additionally or alternatively, the system 1450 can be utilized as part of a treatment procedure, such as to help a physician determine parameters for delivering a therapy to the patient (e.g., delivery location, amount and type of therapy) based on one or more identified connected trajectories.

[0086] As an example, a catheter having one or more therapy delivery devices 1456 affixed thereto can be inserted into a patient’s body 1454 as to contact the patient’s heart 1452, endocardially or epicardially. The placement of the therapy delivery device 1456 can be guided according to the location and characteristics of connected trajectories that have been identified, such as disclosed herein. The guidance can be automated, semi -automated or be manually implemented based on information provided. Those skilled in the art will understand and appreciate various type and configurations of therapy delivery devices 1456 that can be utilized, which can vary depending on the type of treatment and the procedure. For instance, the therapy device 1456 can be configured to deliver electrical therapy, chemical therapy, sound wave therapy, thermal therapy or any combination thereof.

[0087] By way of example, the therapy delivery device 1456 can include one or more electrodes located at a tip of an ablation catheter configured to generate heat for ablating tissue in response to electrical signals (e.g., radiofrequency energy) supplied by a therapy system 1458. In other examples, the therapy delivery device 1456 can be configured to deliver cooling to perform ablation (e.g., cryogenic ablation), to deliver chemicals (e.g., drugs), ultrasound ablation, high-frequency ablation, or a combination of these or other therapy mechanisms. In still other examples, the therapy delivery device 1456 can include one or more electrodes located at a tip of a pacing catheter to deliver electrical stimulation, such as for pacing the heart, in response to electrical signals (e.g., pacing pulses) supplied by the therapy system 1458. Other types of therapy can also be delivered via the therapy system 1458 and the invasive therapy delivery device 1456 that is positioned within the body.

[0088] As a further example, the therapy system 1458 can be located external to the patient’s body 1454 and be configured to control therapy that is being delivered by the device 1456. For instance, the therapy system 1458 includes controls (e.g., hardware and / or software) 1460 that can communicate (e.g., supply) electrical signals via a conductive link electrically connected between the delivery device (e.g., one or more electrodes) 1456 and the therapy system 1458. The control system 1460 can control parameters of the signals supplied to the device 1456 (e.g., current, voltage, repetition rate, trigger delay, sensing trigger amplitude) for delivering therapy (e.g., ablation or stimulation) via the electrode(s) 1456 to one or more location of the heart 1452. The control circuitry 1460 can set the therapy parameters and apply stimulation based on automatic, manual (e.g., user input) or a combination of automatic and manual (e.g., semiautomatic) controls, which may be based on the detection and associated characteristics of connected trajectories on the cardiac envelope. One or more sensors (not shown) can also communicate sensor information from the therapy device 1456 back to the therapy system 1458. The position of the device 1456 relative to the heart 1452 can be determined and tracked intraoperatively via an imaging modality (e.g., fluoroscopy, x-ray), a mapping system 1462, direct vision or the like. The location of the device 1456 and the therapy parameters thus can be combined to determine and control corresponding therapy parameter data.

[0089] Before, during and / or after delivering a therapy via the therapy system 1458, another system or subsystem can be utilized to acquire electrophysiology information for the patient. In the example of FIG. 14, a sensor array 1464 includes one or more electrodes (e.g., the arrangement of physical electrodes 204 of FIG. 2) that can be utilized for recording patient electrical activity. The sensing electrodes that form the array 1464 can be mounted to a substrate (e.g., a wearable garment), be applied in strips of sensing electrodes or individually mounted electrodes. As one example, the sensor array 1464 can correspond to a high-density arrangement of body surface sensors (e.g., greater than approximately 200 electrodes) that are distributed over a portion of the patient’s torso for measuring electrical activity associated with the patient’s heart (e.g., as part of an electrocardiographic mapping procedure), such as described herein. As an example, the sensor array 1464 can be a reduced set of electrodes, which does not cover the patient’s entire torso and is designed for measuring electrical activity for a particular purpose (e.g., an array of electrodes specially designed for analyzing atrial fibrillation and / or ventricular fibrillation) and / or formonitoring electrical activity for a predetermined spatial region of the heart (e.g., atrial region(s) or ventricular region(s)).

[0090] One or more sensors may also be located on the device 1456 that is inserted into the patient’s body. Such sensors can be utilized separately or in conjunction with the non- invasive sensors 1464 for mapping electrical activity for an endocardial surface, such as the wall of a heart chamber, as well as for an epicardial surface. Additionally, such electrode can also be utilized to help localize the device 1456 within the heart 1452, which can be registered into an image or map that is generated by the system 1450. Alternatively, such localization can be implemented in the absence of emitting a signal from an electrode within or on the heart 1452.

[0091] In each of such example approaches for acquiring patient electrical information, including invasively, non-invasively, or a combination of invasive and non-invasive sensing, the sensor array(s) 1464 provides the sensed electrical information to a corresponding measurement system 1466. The measurement system 1466 can include appropriate controls and associated circuitry 1468 for providing corresponding measurement data 1470 that describes electrical activity detected by the sensors in the sensor array 1464. The measurement data 1470 can include analog and / or digital information (e.g., corresponding to physiological data).

[0092] The controls 1468 can also be configured to control the data acquisition process (e.g., sample rate, line filtering) for measuring electrical activity and providing the measurement data 1470. In some examples, the control 1468 can control acquisition of measurement data 1470 separately from the therapy system operation, such as in response to a user input. In other examples, the measurement data 1470 can be acquired concurrently with and in synchronization with delivering therapy by the therapy system, such as to detect electrical activity of the heart 1452 that occurs in response to applying a given therapy (e.g., according to therapy parameters). For instance, appropriate time stamps can be utilized for indexing the temporal relationship between the respective measurement data 1470 and therapy parameters used to deliver therapy as to facilitate the evaluation and analysis thereof.

[0093] Executing the mapping system 1462 causes the processor to combine the measurement data 1470 corresponding to electrical activity of the heart 1452 with geometry data 1472 (e.g., electrode geometry data determined by the method 700 and data describingcardiac geometry) by applying appropriate processing and computations to provide corresponding output data 1474. As an example, the output data 1474 can include one or more graphical maps demonstrating determined arrhythmia drivers with respect to a geometric surface of the patient’s heart 1452 (e.g., information derived from electrical measurements superimposed on a surface of the heart 1452).

[0094] Since the measurement system 1466 can measure electrical activity of a predetermined region or the entire heart concurrently (e.g., where the sensor array 1464 covers the entire thorax of the patient’s body 1454), the resulting output data (e.g., visualizing attributes of identified stable rotors and / or other electrocardiographic maps) 1474 thus can also represent concurrent data for the predetermined region or the entire heart in a temporally and spatially consistent manner. The time interval for which the output data / maps are computed can be selected based on user input (e.g., selecting a timer interval from one or more waveforms). Additionally or alternatively, the selected intervals can be synchronized with the application of therapy by the therapy system 1458.

[0095] For example, executing the electrogram reconstruction code 1480 will cause the processor to compute an inverse solution and provide corresponding reconstructed electrograms based on the electrical measurement data 1470 and the geometry data 1472. The reconstructed electrograms thus can correspond to electrocardiographic activity across a cardiac envelope, and can include static (three-dimensional at a given instant in time) and / or be dynamic (e.g., four-dimensional map that varies over time). Examples of inverse algorithms that can be implemented by electrogram reconstruction 1480 include those disclosed in U.S. Patent Nos. 7,983,743 and 6,772,004. The EGM reconstruction 1480 thus can reconstruct the body surface electrical activity measured via the sensor array 1464 onto a multitude of locations on a cardiac envelope (e.g., greater than 200 locations, such as about 2000 locations or more.

[0096] As disclosed herein, the cardiac envelope can correspond to the 3D body surface geometry of one or more surface regions of a patient’s heart, which region can include epicardial or endocardial surfaces. Alternatively or additionally, the cardiac envelope can correspond to a geometric surface that resides between the epicardial surface of a patient’s heart and the outer surface of the patient’s body where the electrodes that form the sensor array 1464 has been positioned. Additionally, the geometry data 1472 that is utilized by the electrogram reconstruction 1480 can correspond to actual patient anatomical geometry, apreprogrammed generic model or a combination thereof (e.g., a model / template that is modified based on patient anatomy), such as disclosed herein.

[0097] As an example, the geometry data 1472 represents the geometry relationship between the cardiac envelope (e.g., cardiac surface) and the electrodes positioned on the torso surface in a three-dimensional coordinate system. As described herein, the geometry relationship between cardiac envelope and torso surface can be obtained via 3D medical imaging modality, such as CT or MRI, which is performed in the absence of the sensor array being placed on the patient (e.g., the patient 602). An imaging device (e.g., an imaging device 608 of FIG. 7) or a camera (e.g., the camera in the system 612 of FIG. 7) may be utilized to digitize the electrodes position on the patient’s torso and provide a set of point clouds for the surface including electrode locations. In examples when the cardiac geometry and electrode geometry are derived from separate data sources, the physiological data for the cardiac envelope and torso surface are registered together to provide the geometry data 1472.

[0098] As mentioned above, the geometry data 1472 can correspond to a mathematical model, which can be a generic model or a user-specific model that has been constructed based on image data for the patient. Appropriate anatomical or other landmarks, including locations for the electrodes in the sensor array 1464 can be identified in the geometry data 1472 to facilitate registration of the electrical measurement data 1470 and performing the inverse method thereon. The identification of such landmarks can be done manually (e.g., by a person via image editing software) or automatically (e.g., via image processing techniques). By way of further example, the range imaging and generation of the geometry data 1472 may be performed before or concurrently with recording the electrical activity that is utilized to generate the electrical measurement data 1470 or the imaging can be performed separately (e.g., before or after the measurement data has been acquired). In some examples, the electrical measurement data 1470 may be processed by the mapping system to extract localized organized patterns of activity to adjust (refine) the geometry data 1472 over a period of one or more time intervals (e.g., where a model or template is used to provide initial geometry data).

[0099] Following (or concurrently with) determining electrical potential data (e.g., electrogram data computed from non-invasively or from both non-invasively and invasively acquired measurements) across the geometric surface of the heart 1452, the electrogram datacan further undergo signal processing by mapping system 1462 to generate the output data, which may include one or more graphical maps. The mapping system 1462 can include one or more methods that, when executed by the processor, cause the processor to characterize the electrical information across the cardiac envelope.

[0100] Executing an output generator 1484 causes the processor to generate one or more graphical outputs (e.g., waveforms, electroanatomic maps or the like) for display based on the output data 1474. A visualization engine 1488 can control features of the output being displayed. For instance, parameters associated with the displayed graphical output, corresponding to an output visualization of a computed map or waveform, such as including selecting a time interval, temporal and spatial thresholds, as well as the type of information that is to be presented in the display 1494 (e.g., the display 610 of FIG. 6) and the like can be selected in response to a user input via a graphical user interface (GUI) 1490. For example, a user can employ the GUI 1490 to selectively program one or more parameters (e.g., temporal and spatial thresholds, filter parameters and the like) utilized by the one or more methods used to process the electrical measurement data 1470. The mapping system 1462 thus can generate corresponding output data 1474 that can in turn be rendered as a corresponding graphical output in a display 1494, such as including one or more graphical visualizations 1492. For example, the output generator 1484 can generate maps and other output visualizations.

[0101] Additionally, in some examples, the output data 1474 can be utilized by the therapy system 1458. For instance, the control system 1460 may implement fully automated control, semi-automated control (partially automated and responsive to a user input) or manual control based on the output data 1474. In some examples, the control system 1460 of the therapy system 1458 can utilize the output data 1474 to control one or more therapy parameters. As an example, the control system 1460 can control delivery of ablation therapy to a site of the heart (e.g., epicardial or endocardial wall) based on one or more arrhythmia drivers identified by one or more method(s). In other examples, an individual can view the map generated in the display to manually control the therapy system, such as using the identification location of connected trajectories (e.g., the region between connected trajectories) on the graphical map as a treatment site. Other types of therapy and devices can also be controlled based on the output data 1474 and corresponding graphical map 1492.EXAMPLE EMBODIMENTS

[0102] Several aspects of the present technology are set forth in the following numbered examples.

[0103] Example 1. A system comprising: a memory for storing machine-readable instructions; and a processor core for accessing the machine-readable instructions and executing the machine-readable instructions as operations, the operations comprising: generating virtual electrode template data based on virtual electrode layout data and body surface geometry data, wherein the body surface geometry data represents a three- dimensional surface of a patient’s body surface where physical electrodes are placed or being placed, the virtual electrode layout data represents an identity and a virtual layout of physical electrodes placed on or being placed on the patient, and the virtual electrode template data represents the identity and the virtual layout of the virtual electrodes placed on the body surface geometry; and determining physical electrode geometry data to localize and identify each of the physical electrodes in three-dimensional space on the body surface based on the virtual electrode template data.

[0104] Example 2. The system of example 1, wherein the virtual electrode layout data represents the identity and a two-dimensional virtual layout of the virtual electrodes and the body surface geometry data is derived from at least one imaging scan, and generating the virtual electrode template data includes operations further comprises: flattening the body surface geometry data representing the three-dimensional surface of the patient’s body surface to a two-dimensional surface of the patient’s body surface; applying the two- dimensional layout of the virtual electrodes to the two-dimensional surface of the patient’s body surface to provide a two-dimensional virtual placement of the virtual electrodes; and transforming the two-dimensional virtual placement of the virtual electrodes into a three- dimensional virtual placement, corresponding to the virtual electrode template data, which represents the identity and virtual placement of the virtual electrodes on the three- dimensional surface of the patient’s body surface.

[0105] Example 3. The system of example 2, wherein: applying the two-dimensional layout of the virtual electrodes further comprises assigning each of the virtual electrodes in the two-dimensional virtual layout to respective spatial coordinates on the two-dimensional surface of the patient’s body surface to provide two-dimensional virtual placement data representing the identity and two-dimensional location of the virtual electrodes, and the two-dimensional virtual electrode layout is transformed into the three-dimensional virtual electrode template data based on the two-dimensional virtual placement data and the body surface geometry data.

[0106] Example 4. The system according to any of examples 1, 2 or 3, wherein determining the physical electrode data includes operations further comprises: identifying at least three anchor points, wherein an anchor point includes a virtual location of a virtual electrode from the virtual electrode template data and a respective physical location of a physical electrode from the physical electrode geometry data; and determining a transformation matrix based on the at least three anchor points, wherein each of the physical electrodes is localized and identified in a three-dimensional coordinate system to provide the physical electrode geometry data based on applying the transformation matrix to the virtual electrode template data.

[0107] Example 5. The system of example 4, wherein the anchor points are identified in response to the body surface geometry data being derived based on image data acquired by at least one imaging scan of the patient without the physical electrodes placed on the patient’s body surface.

[0108] Example 6. The system of example 4, wherein the operations further comprise: determining an interactive graphical user interface displaying a graphical representation of the virtual layout on the patient’s body surface based on the virtual electrode template data, wherein the at least three anchor points are identified in response to a user input specifying correspondence between locations in the virtual electrode template data and respective locations of the physical electrodes on the patient’s body surface.

[0109] Example 7. The system of example 6, wherein at least one anchor point is identified from an anatomical landmark.

[0110] Example 8. The system of example 4, further comprising a camera adapted to provide image data representing an image of the physical electrodes placed on the patient’s body surface, and wherein the at least three anchor points are manually or automatically selected based on the image data, in which the image data is textured mapped to the body surface.

[0111] Example 9. The system according to any of examples 1, 2 or 3, wherein the virtual electrode template data includes spatial locations of the virtual electrodes represented in a first point cloud and the physical electrode geometry data includes spatial locations ofthe physical electrodes represented in a second point cloud, and the physical electrode geometry data is generated based on registering the first point cloud with the second point cloud to identify each of the respective physical electrodes, such that the determined physical electrode geometry data includes a three-dimensional spatial location and identity for each of the respective physical electrodes.

[0112] Example 10. The system of example 9, wherein the second point cloud is derived based on image data acquired by at least one imaging scan of the patient’s body with the respective physical electrodes or fiducial markers placed on the patient’s body surface.

[0113] Example 11. The system according to any of examples 1, 2 or 3, further comprising: a projector adapted to project a projected image on the patient’s body surface based on the virtual layout data.

[0114] Example 12. The system of example 11, further comprising: a camera adapted to acquire an acquired image of the projected image, wherein the operations further comprise adjusting the projected image based on the acquired image.

[0115] Example 13. A computer-implemented method for electrode localization, the method comprising: generating virtual electrode template data based on virtual electrode layout data and body surface geometry data, wherein the body surface geometry data represents a three-dimensional surface of a patient’s body surface where physical electrodes are placed or being placed, the virtual electrode layout data represents an identity and a virtual layout of physical electrodes placed on or being placed on the patient, and the virtual electrode template data represents the identity and the virtual layout of the virtual electrodes placed on the body surface geometry; and determining physical electrode geometry data to localize and identify each of the physical electrodes in three-dimensional space on the body surface based on the virtual electrode template data.

[0116] Example 14. The method of example 13, wherein the virtual electrode layout data represents the identity and a two-dimensional virtual layout of the virtual electrodes and the body surface geometry data is derived from at least one imaging scan, and generating the virtual electrode template data further comprises: flattening the body surface geometry data representing the three-dimensional surface of the patient’s body surface to a two-dimensional surface of the patient’s body surface; applying the two- dimensional layout of the virtual electrodes to the two-dimensional surface of the patient’sbody surface to provide a two-dimensional virtual placement of the virtual electrodes; and transforming the two-dimensional virtual placement of the virtual electrodes into a three- dimensional virtual placement, corresponding to the virtual electrode template data, which represents the identity and virtual placement of the virtual electrodes on the three- dimensional surface of the patient’s body surface.

[0117] Example 15. The method of example 14, wherein applying the two- dimensional layout of the virtual electrodes further comprises: assigning each of the virtual electrodes in the two-dimensional virtual layout to respective spatial coordinates on the two- dimensional surface of the patient’s body surface to provide two-dimensional virtual placement data representing the identity and two-dimensional location of the virtual electrodes, and transforming the two-dimensional virtual electrode layout into the three- dimensional virtual electrode template data based on the two-dimensional virtual placement data and the body surface geometry data.

[0118] Example 16. The method according to any of examples 13, 14 or 15, wherein determining the physical electrode data further comprises: identifying at least three anchor points, wherein an anchor point includes a virtual location of a virtual electrode from the virtual electrode template data and a respective physical location of a physical electrode from the physical electrode geometry data; and determining a transformation matrix based on the at least three anchor points, wherein each of the physical electrodes is localized and identified in a three-dimensional coordinate system to provide the physical electrode geometry data based on applying the transformation matrix to the virtual electrode template data.

[0119] Example 17. The method of example 16, wherein the anchor points are identified in response to the body surface geometry data being derived based on image data acquired by at least one imaging scan of the patient without the physical electrodes placed on the patient’s body surface.

[0120] Example 18. The method of example 16, further comprising: determining an interactive graphical user interface displaying a graphical representation of the virtual layout on the patient’s body surface based on the virtual electrode template data, wherein the at least three anchor points are identified in response to a user input specifying correspondence between locations in the virtual electrode template data and respective locations of the physical electrodes on the patient’s body surface.

[0121] Example 19. The method of example 18, wherein at least one anchor point is identified from an anatomical landmark based on the image data and responsive to a user input

[0122] Example 20. The method of example 16, further comprising: providing image data acquired by a camera, the image data representing an image of the physical electrodes placed on the patient’s body surface, and wherein the at least three anchor points are manually or automatically selected based on the image data which is texture mapped to the body surface.

[0123] Example 21. The method according to any of examples 13, 14 or 15, wherein the virtual electrode template data includes spatial locations of the virtual electrodes represented in a first point cloud and the physical electrode geometry data includes spatial locations of the physical electrodes represented in a second point cloud, and determining the physical electrode geometry data includes: registering the first point cloud with the second point cloud to identify each of the physical electrodes, such that the determined physical electrode geometry data includes a three-dimensional spatial location and identity for each of the respective physical electrodes.

[0124] Example 22. The method of example 21, further comprising generating the second point cloud based on image data acquired by at least one imaging scan of the patient’s body with the respective physical electrodes or fiducial markers are placed on the patient’s body surface, wherein the second point cloud includes points representative of the respective physical electrodes or fiducial markers on the patient’s body surface.

[0125] Example 23. The method according to any of examples 13, 14 or 15, further comprises: projecting a projected image on the patient’s body surface based on the virtual layout data.

[0126] Example 24. The method of example 23, further comprising: acquiring an acquired image of the projected image; and adjusting the projected image based on the acquired image.

[0127] Example 25. One or more non-transitory machine readable media having instructions, which when executed by one or more processors, are programmed to perform a method according to any of examples 13-24.

[0128] What have been described above are examples. It is, of course, not possible to describe every conceivable combination of components or methodologies, but one ofordinary skill in the art will recognize that many further combinations and permutations are possible. Accordingly, the disclosure is intended to embrace all such alterations, modifications, and variations that fall within the scope of this application, including the appended claims. As used herein, the term "includes" means includes but not limited to, the term "including" means including but not limited to. The term "based on" means based at least in part on. Additionally, where the disclosure or claims recite "a," "an," "a first," or "another" element, or the equivalent thereof, it should be interpreted to include one or more than one such element, neither requiring nor excluding two or more such elements.

[0129] A “value” as used herein may include, but is not limited to, a numerical or other kind of value or level such as a percentage, a non-numerical value, a discrete state, a discrete value, a continuous value, among others. The term “value of X” or “level of X” as used throughout this detailed description and in the claims refers to any numerical or other kind of value for distinguishing between two or more states of X. For example, in some cases, the value of X may be given as a percentage between 0% and 100%. In other cases, the value of X could be a value in the range between 1 and 10. In still other cases, the value of X may not be a numerical value, but could be associated with a given discrete state, such as “not X”, “slightly x”, “x”, “very x” and “extremely x”.

[0130] In this description, unless otherwise stated, "about," "approximately" or "substantially" preceding a parameter means being within + / - 10 percent of that parameter. Modifications are possible in the described embodiments, and other embodiments are possible, within the scope of the claims.

[0131] Further, unless specified otherwise, “first”, “second”, or the like are not intended to imply a temporal aspect, a spatial aspect, an ordering, etc. Rather, such terms are merely used as identifiers, names, etc. for features, elements, items, etc. For example, a first channel and a second channel generally correspond to channel A and channel B or two different or two identical channels or the same channel. Additionally, “comprising”, “comprises”, “including”, “includes”, or the like generally means comprising or including, but not limited to.

[0132] It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example, certain acts or events of any of the processes or methods described herein maybe performed in a different sequence, may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the techniques). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a medical device. In this disclosure, the term “based on” means based at least in part on. Also, in this disclosure the term “in response to” and variants thereof mean in response at least in part to.

[0133] In one or more examples, the described techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include non-transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0134] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

Claims

CLAIMSWhat is claimed is:

1. A system comprising: a memory for storing machine-readable instructions; and a processor core for accessing the machine-readable instructions and executing the machine-readable instructions as operations, the operations comprising: generating virtual electrode template data based on virtual electrode layout data and body surface geometry data, wherein the body surface geometry data represents a three-dimensional surface of a patient’s body surface where physical electrodes are placed or being placed, the virtual electrode layout data represents an identity and a virtual layout of physical electrodes placed on or being placed on the patient, and the virtual electrode template data represents the identity and the virtual layout of the virtual electrodes placed on the body surface geometry; and determining physical electrode geometry data to localize and identify each of the physical electrodes in three-dimensional space on the body surface based on the virtual electrode template data.

2. The system of claim 1, wherein the virtual electrode layout data represents the identity and a two-dimensional virtual layout of the virtual electrodes and the body surface geometry data is derived from at least one imaging scan, and generating the virtual electrode template data includes operations further comprises: flattening the body surface geometry data representing the three-dimensional surface of the patient’s body surface to a two-dimensional surface of the patient’s body surface; applying the two-dimensional layout of the virtual electrodes to the two- dimensional surface of the patient’s body surface to provide a two-dimensional virtual placement of the virtual electrodes; and transforming the two-dimensional virtual placement of the virtual electrodes into a three-dimensional virtual placement, corresponding to the virtual electrode template data,which represents the identity and virtual placement of the virtual electrodes on the three- dimensional surface of the patient’s body surface.

3. The system of claim 2, wherein: applying the two-dimensional layout of the virtual electrodes further comprises assigning each of the virtual electrodes in the two-dimensional virtual layout to respective spatial coordinates on the two-dimensional surface of the patient’s body surface to provide two-dimensional virtual placement data representing the identity and two-dimensional location of the virtual electrodes, and the two-dimensional virtual electrode layout is transformed into the three- dimensional virtual electrode template data based on the two-dimensional virtual placement data and the body surface geometry data.

4. The system according to any of claims 1, 2 or 3, wherein determining the physical electrode data includes operations further comprises: identifying at least three anchor points, wherein an anchor point includes a virtual location of a virtual electrode from the virtual electrode template data and a respective physical location of a physical electrode from the physical electrode geometry data; and determining a transformation matrix based on the at least three anchor points, wherein each of the physical electrodes is localized and identified in a three-dimensional coordinate system to provide the physical electrode geometry data based on applying the transformation matrix to the virtual electrode template data.

5. The system of claim 4, wherein the anchor points are identified in response to the body surface geometry data being derived based on image data acquired by at least one imaging scan of the patient without the physical electrodes placed on the patient’s body surface.

6. The system of claim 4, wherein the operations further comprise: determining an interactive graphical user interface displaying a graphical representation of the virtual layout on the patient’s body surface based on the virtual electrode template data, wherein the at least three anchor points are identified in response to a user input specifying correspondence between locations in the virtual electrode template data and respective locations of the physical electrodes on the patient’s body surface.

7. The system of claim 6, wherein at least one anchor point is identified from an anatomical landmark.

8. The system of claim 4, further comprising a camera adapted to provide image data representing an image of the physical electrodes placed on the patient’s body surface, and wherein the at least three anchor points are manually or automatically selected based on the image data, in which the image data is texture mapped to the body surface.

9. The system according to any of claims 1, 2 or 3, wherein the virtual electrode template data includes spatial locations of the virtual electrodes represented in a first point cloud and the physical electrode geometry data includes spatial locations of the physical electrodes represented in a second point cloud, and the physical electrode geometry data is generated based on registering the first point cloud with the second point cloud to identify each of the respective physical electrodes, such that the determined physical electrode geometry data includes a three-dimensional spatial location and identity for each of the respective physical electrodes.

10. The system of claim 9, wherein the second point cloud is derived based on image data acquired by at least one imaging scan of the patient’s body with the respective physical electrodes or fiducial markers placed on the patient’s body surface.

11. The system according to any of claims 1, 2 or 3, further comprising: a projector adapted to project a projected image on the patient’s body surface based on the virtual layout data.

12. The system of claim 11, further comprising: a camera adapted to acquire an acquired image of the projected image, wherein the operations further comprise adjusting the projected image based on the acquired image.

13. A computer-implemented method for electrode localization, the method comprising: generating virtual electrode template data based on virtual electrode layout data and body surface geometry data, wherein the body surface geometry data represents a three-dimensional surface of a patient’s body surface where physical electrodes are placed or being placed, the virtual electrode layout data represents an identity and a virtual layout of physical electrodes placed on or being placed on the patient, and the virtual electrode template data represents the identity and the virtual layout of the virtual electrodes placed on the body surface geometry; and determining physical electrode geometry data to localize and identify each of the physical electrodes in three-dimensional space on the body surface based on the virtual electrode template data.

14. The method of claim 13, wherein the virtual electrode layout data represents the identity and a two-dimensional virtual layout of the virtual electrodes and the body surface geometry data is derived from at least one imaging scan, and generating the virtual electrode template data further comprises: flattening the body surface geometry data representing the three-dimensional surface of the patient’s body surface to a two-dimensional surface of the patient’s body surface; applying the two-dimensional layout of the virtual electrodes to the two- dimensional surface of the patient’s body surface to provide a two-dimensional virtual placement of the virtual electrodes; and transforming the two-dimensional virtual placement of the virtual electrodes into a three-dimensional virtual placement, corresponding to the virtual electrode template data, which represents the identity and virtual placement of the virtual electrodes on the three- dimensional surface of the patient’s body surface.

15. The method of claim 14, wherein applying the two-dimensional layout of the virtual electrodes further comprises: assigning each of the virtual electrodes in the two-dimensional virtual layout to respective spatial coordinates on the two-dimensional surface of the patient’s body surface to provide two-dimensional virtual placement data representing the identity and two- dimensional location of the virtual electrodes, and transforming the two-dimensional virtual electrode layout into the three- dimensional virtual electrode template data based on the two-dimensional virtual placement data and the body surface geometry data.

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