Determination of Electrode Orientation Using Optimized Imaging Parameters

Abstract

A method performed by a computer for determining the position of a stimulation electrode is disclosed. The method includes determining the orientation of a medical stimulation electrode from medical image data showing an image of the electrode. A first scan is generated in which the position of the electrode is determined, and a second scan having optimized imaging parameters is generated using the same imaging modality or a different imaging modality. The second scan shows, for example, a more accurate image of the electrode and is used to determine the direction of rotation along the longitudinal axis of the electrode.

Description

Technical Field

[0001] The present invention relates to a method for determining the position of a stimulation electrode executed by a computer, a corresponding computer program, a computer-readable storage medium storing such a program, and a computer that executes the program, and also relates to an electronic data storage device and a medical system including the above-described computer.

Background Art

[0002] Currently, the following procedures are known for determining the orientation of a medical stimulation electrode in 3D and 2D medical images.

[0003] An overview of the current procedure for 3D images is as follows. First, a 3D image showing the electrode is created using a medical imaging device (e.g., a CT scanner or an MR scanner). Next, using a computer algorithm, the electrode and specific features such as its tip and longitudinal axis within the 3D image are identified, and if the electrode is not symmetric about the longitudinal axis, its orientation is specified. This orientation can be specified by the asymmetric features of the three-dimensionally reconstructed electrode (e.g., directed contacts and / or specific markers), or by using specific artifacts (e.g., metal artifacts in the CT scanner of contacts and markers) that factor in these asymmetric features. Using the information specified by the algorithm, the spatial position of the electrode in the 3D image is specified.

[0004] An overview of the current procedure for the projected 2D image is as follows. First, to enable localization of electrodes in three-dimensional space, a medical imaging device (e.g., a cone beam CT device) is used to create a series of projection two-dimensional images containing a sufficient number of images showing the electrodes from different angles. These two-dimensional images are co-registered to a common coordinate system so that their relative positions in three-dimensional space can be specified. Next, a computer algorithm is used to identify specific features within the two-dimensional images, such as the electrodes and their tip portions, as well as the longitudinal axis, and, if the electrodes are not symmetric about the longitudinal axis, their orientation. The orientation can be specified, for example, by asymmetric features of the electrodes such as directed contacts and / or specific markers that are differently displayed depending on the various imaging angles used for the two-dimensional images. Based on this information specified by the algorithm, the spatial position of the electrodes in the same three-dimensional coordinate system as the registered two-dimensional images can be determined.

[0005] However, in known approaches, the following applies. · When using a general-purpose scan (e.g., a head CT overview scan), the resolution is limited for efficiency (scan time, size of the image set) and / or to minimize the X-ray dose. · This limitation in image resolution reduces the accuracy of electrode localization, especially when the electrodes are small. · Considering the above drawbacks, this accuracy may be improved at a higher resolution. Due to the limitations of the device (maximum volume * resolution), it may not be possible to create a scan at a high enough resolution to show the electrodes in their overall shape (which is necessary to determine the complete position of the implant) while simultaneously identifying features for accurately specifying the tip portion and especially the orientation of the electrodes. SUMMARY OF THE INVENTION

[0006] An object of the present invention is to provide a means for more accurately determining the orientation of a medical stimulation electrode from a medical image.

[0007] The present invention can be used for procedures related to systems for planning and re-evaluating the position of electrodes, such as Brainlab Elements Trajectory Planning for example.

[0008] Aspects, embodiments and exemplary steps of the present invention and their implementations are disclosed below. Various exemplary features of the present invention can be combined in accordance with the present invention if they are technically advantageous and feasible.

[0009] (Brief Exemplary Description of the Invention) The following briefly describes specific features of the present invention. However, this does not limit the present invention to only the features or combinations of features described in this section.

[0010] The disclosed method includes determining the orientation of a medical stimulation electrode from medical image data showing an image of the electrode. A first scan is generated in which the position of the electrode is determined, and a second scan with optimized imaging parameters is generated using the same imaging modality or a different imaging modality. The second scan shows, for example, a more accurate image of the electrode and is used to determine the rotational direction of the electrode along its longitudinal axis.

[0011] (General Description of the Invention) In this section, the general features of the present invention will be described with reference to possible embodiments of the present invention, for example.

[0012] Generally, in a first aspect, the present invention achieves the aforementioned object by providing a medical method executed by a computer for determining the position of a stimulation electrode. This method includes at least one processor of at least one computer (for example, at least one computer is part of a navigation system) executing the following exemplary steps executed by the at least one processor.

[0013] In an exemplary (e.g., first) step, first medical image data is obtained that describes an anatomical body part and a first digital medical image of a stimulating electrode. For example, the first digital medical image is a three-dimensionally defined digital image, such as a tomographic image, e.g., computed tomography, magnetic resonance tomography, ultrasonic tomography, or the first digital medical image is a two-dimensional digital image, such as an X-ray. For example, the stimulating electrode includes at least two directed contacts spaced apart from each other, and at least a portion of the image appearance of at least two spaces between the at least two directed contacts in the second digital medical image is used to determine a rotational orientation described by the electrode orientation data. This can be done as described in European Patent No. 3376960, which is hereby incorporated by reference in its entirety. The method disclosed therein specifically includes obtaining rotational image data that describes (e.g., defines or represents, at least one of) a two-dimensional medical image of an anatomical structure (i.e., an anatomical body part) and a stimulating electrode. Specifically, the (e.g., respective) two-dimensional images depict both the anatomical body part and the stimulating electrode. The two-dimensional medical image is taken or being taken by a two-dimensional medical imaging device or method, such as imaging by a C-arm (also called C-arm X-ray, C-arm radiography), imaging by rotational angiography, imaging by cone-beam computed tomography (cone-beam CT). For example, the two-dimensional image is taken or being taken during rotation of the medical imaging device relative to the anatomical body part. That is, each two-dimensional image is taken at a different rotational position of the medical imaging device relative to the position of the anatomical body part and the stimulating electrode, and for example, the position immediately after the medical imaging device is associated with the two-dimensional image taken immediately after in its production order. For example, each two-dimensional medical image is associated with a different imaging perspective (e.g., relative to the position of the anatomical structure). The rotational image data further describes, for each of the two-dimensional medical images, the imaging perspective relative to the anatomical body part associated with each two-dimensional medical image.The imaging viewpoints are preferably defined by the anatomical body part and the position of the medical imaging device relative to, for example, the electrodes when each two-dimensional image is generated.

[0014] For example, determining the orientation data of the electrodes includes determining the image appearance of the orientation markers based on the first medical image data, for example, by at least one of the following. · Segmenting the image appearance of the electrodes in each first digital medical image. · Detecting the edges of the components of the first digital medical image. · Comparing the image appearance of the electrodes in the second digital medical image with predetermined electrode template data acquired prior to describing the structural data of the stimulating electrode.

[0015] In the case of a cone beam CT scanner, the orientation of the stimulating electrode is determined, for example, by first creating a limited number of schematic two-dimensional images of the electrode projected from different angles (e.g., every 30 degrees). The electrodes are localized on these images by an algorithm, and the features of the electrodes are analyzed. This analysis determines which angle is effective for more accurate localization of the electrodes. An example of such a feature is the shape of a rotationally asymmetric marker. This shape looks different from different angles. For example, it may look flatter from one angle and thicker from another angle. For example, if the orientation is determined by finding the angle orthogonal to the flat surface of the marker, the interesting angles for the next series of two-dimensional images may be around the angle of the current two-dimensional image where the flattest shape is seen. With this information, a second series of two-dimensional images can be created using parameters (dose, field of view (FOV), focus, collimator settings) optimized to achieve accurate electrode localization.

[0016] In an exemplary (e.g., second) step, electrode position data is determined based on the first medical image data. Here, the electrode position data describes the position of the stimulation electrode with respect to an anatomical body part. For example, this position is determined by analyzing (e.g., segmenting) the first digital medical image with respect to the position of the imaging artifact resulting from and / or associated with the stimulation electrode. For example, the electrode position data is determined by determining the position of an artifact in the first medical image that represents the imaging response of the stimulation electrode to the imaging radiation used to generate the first medical image data.

[0017] In an exemplary (e.g., third) step, second digital medical image data is acquired based on the electrode position data. Here, the second digital medical image data describes, for example, a set of second digital medical images of the stimulation electrode imaged from a plurality of different imaging directions with respect to the stimulation electrode. For example, the second digital medical image is a three-dimensionally defined digital image such as a tomographic image such as computed tomography, magnetic resonance tomography, or ultrasonic tomography, or the second digital medical image is a two-dimensional digital image such as an X-ray photograph. The imaging geometry used to generate the second digital medical image data is determined based on the electrode position data such that an image rendering of the electrode in the second digital medical image is generated. For example, at least one of the imaging directions in which the second digital medical image is generated is determined based on the first medical image data. For example, at least one imaging direction is perpendicular to the longitudinal axis of the stimulation electrode.

[0018] In an exemplary (e.g., fourth) step, electrode orientation data is determined based on the second digital medical image data. Here, the electrode orientation data describes the orientation of the rotation about the longitudinal axis of the electrode. For example, the orientation of the electrode is determined based on the second digital medical image data, whereby the orientation can be determined more accurately than by determining the orientation based on the first medical image data.

[0019] In an example of the method according to the first aspect, at least one of the first medical image data or the second digital medical image data is three-dimensional image data, such as, for example, tomographic image data. In an example of the method according to the first aspect, at least one of the first medical image data or the second digital medical image data is two-dimensional image data (for example, an X-ray photograph).

[0020] In an example of the method according to the first aspect, in order to generate third medical image data that describes, for example, a third medical image of a stimulation electrode, the imaging parameters of the medical imaging device are optimized based on at least one of the first medical image data or the second digital medical image data. For example, the imaging parameters are at least one of the imaging radiation dose, the field of view, the focal point, or the collimator setting of the medical imaging device used to generate at least one of the first medical image data, the second medical image data, and the third medical image data. For example, the third medical image data is two-dimensional or three-dimensional image data (for example, data obtained by X-ray imaging or tomographic imaging).

[0021] In a second aspect, the present invention relates to a computer program comprising instructions which, when executed by at least one computer, cause the at least one computer to execute the method in the first aspect. Alternatively or additionally, the present invention may relate to a signal wave (physical, e.g., electrical, e.g., engineer-generated), e.g., a digital signal wave (e.g., an electromagnetic carrier wave carrying information representing a program (e.g., the program described above)), comprising code means suitable for performing any or all of the steps of the method in the first aspect. The signal wave is, by way of example, a data carrier wave signal carrying the computer program described above. A computer program stored on a disk is a data file which, when read out and transmitted, becomes a data stream, e.g., in the form of a signal (physical, e.g., electrical, e.g., engineer-generated). This signal can be implemented as a signal wave, e.g., an electromagnetic carrier wave as described herein. For example, the signal (e.g., signal wave) is configured to be transmitted via a computer network (e.g., LAN, WLAN, WAN, mobile network, e.g., the Internet). For example, the signal (e.g., signal wave) is configured to be transmitted by optical or acoustic data transmission. Thus, the present invention in the second aspect may alternatively or additionally relate to a data stream representing the program described above, i.e., a data stream constituting the program.

[0022] In a third aspect, the present invention relates to a computer-readable storage medium storing the program in the second aspect. The storage medium of this program is, for example, non-transitory.

[0023] In a fourth aspect, the present invention is directed to at least one computer (e.g., one computer) including at least one processor (e.g., one processor) that executes the program in the second aspect, or at least one computer (e.g., one computer) including a computer-readable storage medium in the third aspect.

[0024] In a fifth aspect, the present invention is a medical system, a) at least one computer in the fourth aspect, wherein the processor is configured to determine the image appearance of the orientation marker by comparing the image appearance of the electrode in the second digital medical image with a predetermined electrode template data acquired previously describing the structural data of the stimulating electrode, based on at least one processor and, for example, rotational image data, b) an electronic data storage device storing at least the electrode template data, c) a first medical imaging device configured to generate first medical image data, and d) a second medical imaging device configured to generate second digital medical image data, comprising The at least one computer is operatively coupled to the first medical imaging device that acquires the first medical image data from the first medical imaging device, operatively coupled to the second medical imaging device that acquires the second digital medical image data from the second medical imaging device, and operatively coupled to at least one electronic data storage device that acquires at least the electrode template data from the data storage device. It is a medical system.

[0025] In an example of the system in the fifth aspect, the first medical imaging device and the second medical imaging device are the same, that is, the system includes only one medical imaging device.

[0026] For example, the present invention does not involve, or is not particularly composed of, or does not include invasive steps corresponding to substantial physical interference with the body, even when it requires medical knowledge specialized for implementation and is implemented with the required specialized considerations and knowledge, and is accompanied by substantial health risks.

[0027] For example, the present invention does not include steps such as embedding stimulating electrodes in anatomical body parts. More specifically, the present invention does not involve, or is not particularly composed of, or does not include any surgical or therapeutic activities. For this reason alone, implementing the present invention does not require, or mean, surgical or therapeutic activities, particularly surgical or therapeutic steps.

[0028] (Definition) In this section, definitions of specific terms used in this disclosure are provided, which also form part of this disclosure.

[0029] The method according to the present invention is, for example, a method executed by a computer. For example, all steps or only some (i.e., a number less than the total number of steps) of the steps of the method according to the present invention can be executed by a computer (for example, at least one computer). One embodiment of the method executed by a computer is the use of a computer for executing a data processing method. An embodiment of the method executed by a computer is a method related to the operation of a computer such that the computer is operated to execute one, a plurality, or all steps of the method.

[0030] A computer includes, for example, at least one processor and, for example, at least one memory for processing data (engineered), for example, electronically and / or optically. The processor is made of, for example, a semiconductor, for example, a semiconductor doped at least partially n-type and / or p-type, for example, at least one of semiconductor materials of Group II, III, IV, V, VI, for example, a substance or composition made of (doped) silicon and / or gallium arsenide. The described calculation or determination steps are, for example, executed by a computer. The determination step or calculation step is, for example, a step of determining data within the framework of a technical method (for example, within the framework of a program). A computer is any kind of data processing device, for example, an electronic data processing device. A computer may be a device generally considered a computer, such as a desktop PC, notebook, netbook, etc., but may also be any programmable device, such as a mobile phone or an embedded processor. A computer may, for example, include a system (network) of "sub-computers" each of which corresponds to a computer itself. The term "computer" includes cloud computers, for example, cloud servers. The term "computer" includes server resources. The term "cloud computer" includes, for example, a cloud computer system composed of at least one cloud computer and a system of a plurality of operably interconnected cloud computers, such as a server farm. Such a cloud computer is preferably connected to a wide area network such as the World Wide Web (WWW) and is placed in the so-called cloud of computers all connected to the World Wide Web. Such infrastructure is used for "cloud computing". "Cloud computing" means computing, software, data access, storage services where the end user does not need to know the physical location and / or configuration of the computer providing a particular service.For example, the term "cloud" is used as a metaphor for the Internet (World Wide Web). For example, the cloud provides computing infrastructure as a service (IaaS). A cloud computer can function as a virtual host for an operating system and / or data processing application used to execute the method of the present invention. A cloud computer is, for example, the Elastic Compute Cloud (EC2) provided by Amazon Web Services. A computer includes, for example, an interface for receiving or outputting data and / or performing analog / digital conversion. The data is, for example, data representing physical characteristics and / or data generated from engineering signals. Engineering signals are generated, for example, by (engineering) detection devices (such as devices for detecting marker devices) and / or (engineering) analysis devices (such as devices for performing (medical) imaging methods). Engineering signals are, for example, electrical signals or optical signals. Engineering signals represent, for example, data received or output by a computer. The computer is preferably operably coupled to a display device that enables the information output by the computer to be displayed, for example, to a user. An example of a display device is a virtual reality device or an augmented reality device (also called virtual reality glasses or augmented reality glasses) that can be used as "Google" for navigation. A specific example of such augmented reality glasses is Google Glass (a trademark of Google Inc.). An augmented reality device or a virtual reality device can be used both for inputting information to a computer through interaction with the user and for displaying the information output by the computer. Another example of a display device includes a standard computer monitor including a liquid crystal display operably coupled to a computer for receiving display control data from the computer to generate a signal for displaying image information content on the display device. A specific embodiment of such a computer monitor is a digital light box.As an example of such a digital light box, there is Buzz (registered trademark), a product of Brainlab AG. The monitor may also be a monitor of a portable (e.g., mobile) device such as a smartphone, a personal digital assistant, or a digital media player.

[0031] The present invention also relates to a computer program including instructions that cause a computer to execute one or more methods (e.g., steps of one or more methods) described herein when the computer executes the program. And / or, the present invention relates to a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) on which the program is stored. And / or, the present invention relates to a computer including the program storage medium. And / or, the present invention relates to a signal wave (e.g., a digital signal wave) (physical, e.g., electrical, e.g., engineer-generated). This signal is, for example, an electromagnetic carrier wave that carries information representing a program (e.g., the program described above), and the information representing the program includes, for example, code means suitable for executing any or all steps of the method described herein. The signal wave is, as an example, a data carrier signal that carries the computer program described above. The present invention also relates to a computer including at least one processor and / or the computer-readable storage medium described above and, for example, a memory, and the processor executes the program.

[0032] In the framework of the present invention, a computer program element can be embodied by hardware and / or software (including firmware, resident software, microcode, etc.). In the framework of the present invention, a computer program element can take the form of a computer program product, and this computer program product can be embodied by a computer-usable (e.g., computer-readable) data storage medium. This data storage medium contains computer-usable (e.g., computer-readable) program instructions ("code" or "computer program"), and the program instructions are embodied in the above data storage medium for use on or in relation to an instruction execution system. Such a system may be a computer. The computer may be a data processing device including means for executing a computer program element and / or program according to the present invention. This data processing device includes, for example, a digital processor (central processing unit or CPU) for executing a computer program element, and optionally, a volatile memory (e.g., random access memory or RAM) for storing data used for executing a computer program element and / or data generated by executing a computer program element. In the framework of the present invention, a computer-usable (e.g., computer-readable) data storage medium may be any data storage medium that can store, communicate, propagate, or carry a program for use on or in relation to an instruction execution system, instruction execution apparatus, or instruction execution device. A computer-usable (e.g., computer-readable) data storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a propagation medium such as the Internet, for example, but is not limited thereto.A computer-usable or computer-readable data storage medium can even be, for example, paper printed with a program or other suitable medium. This is because the program can be electronically captured, for example, by optically scanning paper or other suitable medium, and then can be compiled, interpreted, or processed in a suitable manner. The data storage medium is preferably a non-volatile data storage medium. The computer program product and any software and / or hardware described herein form various means for performing the functions of the present invention in exemplary embodiments. The computer and / or data processing device may include, for example, a guidance information device including means for outputting guidance information. The guidance information can be output to the user visually, for example, by visual indication means (such as a monitor and / or a lamp), and / or acoustically, for example, by acoustic indication means (such as a speaker and / or a digital voice output device), and / or haptically, for example, by haptic indication means (such as a vibration element, or a vibration element incorporated in an instrument). For the purposes of this document, the computer is an engineering (e.g., tangible) computer including, for example, engineering components such as mechanical and / or electronic components. The devices described as such in this document are engineering, e.g., tangible, devices.

[0033] For example, the expression "acquire data" includes cases where data is determined by a method or program executed by a computer (within the framework of a method executed by a computer). For example, determining data includes measuring a physical quantity, converting a measurement value into data (e.g., digital data), and / or a computer calculating (and, for example, outputting) data, for example, within the framework of a method according to the present invention. The "determine / judge / discriminate" step described herein includes, for example, issuing a command to execute a determination (or judgment or discrimination; hereinafter, the combined description of judgment and discrimination is omitted) described herein, or is composed of issuing a command. For example, this step includes issuing a command to cause a computer, for example, in the cloud, for example, a remote computer, for example, a remote server, to execute a determination, or is composed of issuing such a command. Alternatively or in addition, the "determination" step described herein includes, for example, receiving data resulting from a determination described herein, for example, receiving the resulting data from a remote computer (for example, the one that caused the determination to be executed). The meaning of "acquire data" includes, for example, cases where data is received or acquired (e.g., input to a computer) by a method or program executed by a computer for further processing by a method or program executed by the computer, for example, from another program, a previous step of a method, or a data storage medium. The generation of the acquired data may be part of a method according to the present invention, but it is not necessary. Therefore, the expression "acquire data" may, for example, mean waiting to receive data and / or receiving data. The received data may be input via an interface, for example.Also, the expression "acquire data" may mean that a method or program executed by a computer performs steps for (actively) receiving or acquiring data from a data source, such as a data storage medium (e.g., ROM, RAM, database, hard drive, etc.), or via an interface (e.g., from another computer or network). Each of the data acquired by the disclosed method or apparatus may be acquired from a database disposed in a data storage device operably connected to a computer for data transfer between the database and the computer (e.g., from the database to the computer). The computer acquires data for use as an input to the step of determining data. The determined data is output again to the same or another database and stored for later use. The database or databases used to execute the disclosed method may be disposed in a network data storage device or network server (e.g., a cloud data storage device or cloud server) or a local data storage device (such as a mass storage device operably connected to at least one computer executing the disclosed method). The data can be made "usable" by performing additional steps before the acquisition step. According to this additional step, data is generated for acquisition. The data is detected or captured, for example, by an analyzer. Alternatively or in addition, the data is input according to an additional step, for example via an interface. The generated data is input, for example, to a computer. By performing an additional step of storing the data in a data storage medium (e.g., ROM, RAM, CD, and / or hard drive, etc.) according to an additional step (preceding the acquisition step), the data can also be provided for use within the framework of the method or program according to the present invention. Thus, the step of "acquire data" can also include instructing a device to acquire and / or provide the data to be acquired.In particular, the acquisition step represents a substantial physical interference with the body, requires specialized medical knowledge to perform, and does not involve invasive steps that pose a substantial health risk even when performed with the necessary specialized care and expertise. In particular, the step of acquiring data (e.g., the step of determining data) does not involve surgical steps and, in particular, does not involve the step of treating the human or animal body using surgery or a therapy. To distinguish the different data used in the method, the data is denoted (i.e., referred to) as "XY data" etc. and is defined with respect to the information that they describe (and thus are preferably referred to as "XY information" etc.).

[0034] In the medical field, imaging methods (also referred to as imaging modalities and / or medical imaging modalities) are used to generate image data of anatomical structures (such as soft tissues, bones, organs, etc.) of the human body (for example, two-dimensional or three-dimensional image data). The term "medical imaging method" means, for example, imaging methods (such as so-called medical imaging modalities and / or radiographic imaging methods) based on devices, such as computed tomography (CT) and cone beam computed tomography (CBCT, for example volumetric (volumetric) CBCT), X-ray tomography, magnetic resonance tomography (MRT or MRI), conventional X-ray examinations, sonography, and / or ultrasound examinations, as well as positron emission tomography. For example, medical imaging methods are performed by an analysis device. According to Wikipedia, examples of medical imaging modalities applied in medical imaging methods include radiography, magnetic resonance imaging, medical ultrasound examination or ultrasound, endoscopy, elastography, tactile imaging, thermography, medical photography, and nuclear medicine functional imaging methods such as positron emission tomography (PET) and single photon emission computed tomography (SPECT). The image data thus generated is also referred to as "medical image data". In an imaging method based on a device, an analysis device is used, for example, to generate image data. The imaging method is used, for example, in medical diagnosis to analyze an anatomical body part in order to generate an image described by the image data. The imaging method is also used, for example, to detect pathological changes in the human body. However, some changes in anatomical structures (for example, pathological changes in structures (tissues)) may not be detectable, for example, may not be visible in the images generated by the imaging method. A tumor is an example of a change in an anatomical structure. When a tumor grows, it can be said to correspond to an enlarged anatomical structure. This enlarged anatomical structure may not be detectable, for example, only a part of the enlarged anatomical structure may be detectable. For example, a primary / malignant brain tumor is usually visualized on an MRI scan when infiltrated with a contrast agent into the tumor. The MRI scan is an example of an imaging method.In the case of such an MRI scan of a brain tumor, the signal enhancement in the MRI image (due to the infiltration of the contrast agent into the tumor) is considered to represent a solid tumor mass. Thus, the tumor is detectable and distinguishable, for example, in the images generated by the imaging method. In addition to such tumors called "enhancing" tumors, about 10% of brain tumors are considered to be indistinguishable by scans and invisible to a user viewing an image generated by an imaging method, for example.

[0035] Image fusion includes elastic image fusion and rigid body image fusion. In the case of rigid body image fusion, the relative positions between pixels of a 2D image and / or between voxels of a 3D image are fixed, but in the case of elastic image fusion, the relative positions may change. In the present application, the term "image morphing" is also used as an alternative to the term "elastic image fusion", and they have the same meaning.

[0036] The elastic fusion transformation (e.g., elastic image fusion transformation) is designed, for example, to allow a seamless transition from one data set (e.g., a first data set, such as a first image) to another data set (e.g., a second data set, such as a second image). The transformation is designed, for example, such that one of the first and second data sets (images) is deformed, for example, such that corresponding structures (e.g., corresponding image elements) are located in the same position as in the other of the first and second images. The deformed (transformed) image from one of the first and second images is, for example, as similar as possible to the other of the first and second images. Preferably, a (numerical) optimization algorithm is applied to find the transformation that results in an optimal similarity. The similarity is preferably measured by a similarity measure (hereinafter also referred to as "similarity measure"). The parameters of the optimization algorithm are, for example, vectors of the deformation field. These vectors are determined by the optimization algorithm to result in an optimal similarity. The optimal similarity thus represents a condition, for example a constraint, of the optimization algorithm. The bottom of the vector is, for example, at the voxel position of one of the first and second images to be transformed, and the tip of the vector is at the corresponding voxel position of the transformed image. A number of these vectors are preferably provided (e.g. more than 20, 100, 1000, 10000, etc.). Preferably, there are (other) constraints on the transformation (deformation), for example to avoid pathological deformations (e.g. deformations in which all voxels are moved to the same position by the deformation). These constraints include, for example, the constraint that the transformation is regular, which means, for example, that the Jacobian determinant calculated from the matrix of the deformation field (e.g. vector field) is greater than zero, and also the constraint that the transformed (deformed) image does not self-intersect, and, for example, that the transformed (deformed) image does not contain any faults and / or fractures. Constraints include, for example, the constraint that a regular grid is not allowed to interfere at any of its positions if it is simultaneously deformed in a corresponding manner with the image.Optimization problems are solved, for example, iteratively by an optimization algorithm, such as a first-order optimization algorithm like the gradient descent algorithm. Other examples of optimization algorithms include optimization algorithms that do not use differentiation, such as the downhill simplex algorithm, or algorithms that use higher-order differentiation, such as a Newton-like algorithm. The optimization algorithm preferably performs local optimization. If there are multiple local optimum values, global algorithms such as simulated annealing or general algorithms can be used. In the case of a linear optimization problem, for example, the simplex method can be used.

[0037] In a step of the optimization algorithm, the voxel is shifted by one unit size, for example, in a direction such that the similarity increases. This size is preferably less than a predetermined limit value, for example, less than one tenth, one hundredth, one thousandth of the diameter of the image, and further, for example, approximately equal to or less than the distance between adjacent voxels. For example, due to a large number of (iterative) steps, large deformations can be carried out.

[0038] The determined elastic fusion transformation can be used, for example, to determine the similarity (or measure of similarity, see above) between a first dataset and a second dataset (a first image and a second image). For this purpose, the deviation between the elastic fusion transformation and the identity transformation is determined. The degree of deviation can be calculated, for example, by determining the difference between the determinant of the elastic fusion transformation and the identity transformation. The higher the deviation, the lower the similarity, and thus the degree of deviation can be used to determine a measure of similarity.

[0039] The measure of similarity can be determined, for example, based on the determined correlation between the first dataset and the second dataset.

[0040] The present invention will be described below with reference to the accompanying drawings. The accompanying drawings illustrate the background of the present invention and represent specific embodiments of the present invention. However, the scope of the present invention is not limited to the specific features disclosed in the context of the figures.

Brief Description of the Drawings

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Modes for Carrying Out the Invention

[0042] FIG. 1 shows the basic steps of the method in the first aspect. Step S11 includes acquiring first medical image data, step S12 includes determining electrode position data, and the subsequent step S13 includes acquiring second medical image data. In step S14, electrode orientation data is determined.

[0043] FIG. 2 shows an embodiment of the present invention that includes all the essential features of the present invention. In this embodiment, the computer 5 executes the entire data processing that is part of the method in the first aspect. Reference numeral 1 indicates the input of data obtained by the method in the first aspect to the computer 5, and reference numeral 3 indicates the output of data determined by the method in the first aspect.

[0044] To overcome the drawbacks of existing solutions, the electrode localization step is performed in a step-by-step manner, enabling high-precision localization while keeping the X-ray exposure dose for imaging close to or below that of existing solutions.

[0045] This is achieved in a computed tomography (CT) or magnetic resonance (MR) scanner by first performing a standard (low-resolution, with other standard parameters) scan to create a general three-dimensional image set showing the electrodes (or a low-resolution scan, as this is sufficient for this step of implant localization). Based on this three-dimensional image set, the position of the electrodes is roughly or as accurately as possible with the available image quality determined by an algorithm. Using the obtained position data of the implant in the scanner coordinate system, a second scan is initiated, limited to the area necessary to image the electrode portions required for high-precision spatial localization. In the case of a CT scan, this may be, for example, just a few image slices (cross-sections) of the position of the tip of the implant and a few slices of the markers (or asymmetric contacts). These slices may be images using a set of scan parameters optimized for implant localization. These scan parameters are high dose, small slice distance, no metal artifact reduction, optimized beam hardening, axial rather than spiral, gantry tilt, couch position, collimator settings, etc. The second set of 3D images may then be aligned with the first set of images (e.g., by a registration algorithm such as mutual information, by using the scanner information of the images to inform the registration algorithm, if the patient did not move between the two scans, they are already in the same correct coordinate system, by using a localizer that uses tracking on the components of the scanner). In the second set of images, detailed information such as the tip of the implant, the shape of the markers, and the artifacts of the contacts can be used to very accurately determine the spatial position of the tip and the orientation of the implant. This is shown in the flowchart of FIG. 3.

[0046] In the case of a cone beam CT scanner, this is achieved by first creating a limited number of summary two-dimensional images of the electrodes projected from a plurality of different angles (e.g., every 30 degrees). On these images, the electrodes are localized by an algorithm and the characteristics of the electrodes are analyzed. Based on this analysis, it is determined which angles are effective for more accurate localization of the electrodes. An example of such a characteristic is the shape of a rotationally asymmetric marker. This may appear flatter from one angle and thicker from another angle. For example, if the current orientation is determined by finding the angle orthogonal to the flat surface of the marker, then for the next series of two-dimensional images, the angles of interest may be around the angle of the current two-dimensional image where the flattest shape is seen. Based on this information, a second series of two-dimensional images can also be created using parameters (dose, field of view (FOV), focus, collimator settings) optimized to achieve accurate electrode localization.

[0047] FIG. 4 is a diagram schematically showing a medical system 4 in a fifth aspect. This system is generally indicated by reference numeral 4 and includes a computer 5 and an electronic data storage device (such as a hard disk) 6 for storing at least first medical image data and second medical image data. The computer 5 is operably coupled to a first medical imaging device 7 and a second medical imaging device 8. The components of the medical system 4 have the functions and characteristics described above with respect to the fifth aspect of the present disclosure.

[0048] FIGS. 5 to 10 show specific embodiments of the detection of directed deep brain stimulation (DBS) electrodes by a mobile computed tomography scanner Loop-X (registered trademark) provided by Brainlab AG. The outline of the problem to be solved is as follows. Although directed DBS electrodes have significant advantages over conventional electrodes, it is very difficult for a neurologist to plan. To simplify the planning, it is desirable to accurately know the position of the electrode, i.e., the position (e.g., the tip) and the orientation (i.e., the rotation) with respect to the patient's anatomical structures. It takes several days after implantation until the electrode settles in a stable position within the patient's brain.

[0049] The current method for determining the orientation of the electrodes is as follows. A few days after implantation, a 3D CT scan is taken. Software that identifies the position of the electrodes from the obtained images accurately detects the position of the electrodes and estimates the direction of the directed (directional) electrodes. Localization is performed based on the artifacts caused by the electrodes during the scan (basically, the weaknesses of the CT scanner are used for this purpose). Such artifacts are depicted in Figure 5, and Figure 6 shows the definition of the position of the tip of the electrode, the direction of the electrode, and the orientation of the electrode.

[0050] The proposed solution using Loop-X® has the following features. Loop-X® is used to generate postoperative electrode detection scans. Loop-X® can take 3D CT images (cone beam CT) and 2D X-ray images. By robotically controlling Loop-X®, for example, the direction can be selected in a 3D scan and the 2D X-ray irradiated in that direction can be obtained. Figure 7 is an explanatory diagram of rotational imaging using Loop-X®.

[0051] The workflow for automatically detecting the position and rotation of the directed DBS electrodes includes the following steps. 1. 3D scan the patient's head (Loop-X® knows the location scanned in its own coordinate system). 2. Apply the conventional approach to detect the position of the electrodes in the 3D scan (see Figure 8) 3. As shown in Figure 9, apply a conventional approach based on artifacts or a new approach using specific presets of Loop-X® to estimate the direction of the electrodes. 4. Automatically take X-ray images in the optimal direction. · Within that range, take multiple X-ray images around the electrodes. · Optimize the distribution and number of shots based on the detection results. · Minimize the radiation dose to the patient. Identify the direction of the electrodes during 5.2D scanning. · Detect a direction marker (such as shown in Fig. 10), or a unique shape indicating the direction. · Use classical image processing or machine learning. · Loop-X (registered trademark) knows the shooting that shows the "best X-ray image". · Calculate the direction of the electrodes in the 3D scan and save the result.

[0052] The technical advantage related to the new approach is not only to estimate the direction of the electrodes, but also to accurately detect it. This new approach may increase the accuracy of determining the direction of the electrodes.

Claims

1. A medical method executed by a computer to determine the position of a stimulating electrode, comprising: a) obtaining first medical image data (S11) describing an anatomical body part and a first digital medical image of the stimulating electrode; b) determining electrode position data (S12) based on the first medical image data, the electrode position data describing the position of the stimulating electrode relative to the anatomical body part; c) obtaining second digital medical image data (S13) based on the electrode position data, the second digital medical image data describing a set of second digital medical images of the stimulating electrode; d) determining electrode orientation data (S14) based on the second digital medical image data.

2. The method according to claim 1, wherein at least one of the first medical image data or the second digital medical image data is three-dimensional image data, such as tomographic image data.

3. The method according to claim 1 or 2, wherein at least one of the first medical image data or the second digital medical image data is two-dimensional image data, such as radiographic image data.

4. The method according to any one of claims 1 to 3, wherein the electrode position data is determined by determining the position of an artifact in the first medical image representing the imaging response of the stimulating electrode to the imaging radiation used to generate the first medical image data.

5. The method according to any one of claims 1 to 4, wherein the stimulating electrode includes at least two directed contacts spaced apart from each other, and the image appearance in at least a part of each of at least two spaces between the at least two directed contacts in the second digital medical image is used to determine a rotational orientation described by the electrode orientation data.

6. The step of determining the electrode orientation data includes: at least one processor, based on the first medical image data, for example: - segmenting the image appearance of the electrode in each of the first digital medical images; - detecting the edges of the components of the first digital medical image; - Comparing the appearance of the electrodes in the second digital medical image with predetermined electrode template data acquired prior to describing the structural data of the stimulation electrodes; The method according to any one of claims 1 to 5, comprising determining the appearance of the image of the orientation marker picture by at least one of the above.

7. The method according to any one of claims 1 to 6, wherein at least one imaging direction in which the second digital medical image is generated is determined based on the first medical image data.

8. The method according to claim 7, wherein the at least one imaging direction is perpendicular to the longitudinal axis of the stimulation electrode.

9. The imaging parameters of the medical imaging device are optimized based on at least one of the first medical image data or the second digital medical image data, for example, to generate third medical image data describing a third medical image of the stimulation electrode. The method according to any one of claims 1 to 8.

10. The method according to claim 9, wherein the imaging parameters are at least one of imaging radiation dose, field of view, focus, or collimator setting.

11. The method according to claim 9, wherein the third medical image data is two-dimensional image data or three-dimensional image data, for example, by X-ray imaging or tomography.

12. A computer program including instructions for causing a computer to execute the method according to any one of claims 1 to 11 when executed by the computer.

13. A computer-readable storage medium storing the program according to claim 12.

14. At least one computer including the storage medium according to claim 13 of the program, wherein the processor is configured to execute the program.

15. A data carrier signal for transmitting the program according to claim 12.

16. A data stream including the program according to claim 12.

17. A medical system (4), a) At least one computer (5) according to claim 14, wherein at least one processor is configured to determine the image appearance of the orientation marker by comparing the image appearance of the electrodes in the second digital medical image with predetermined electrode template data acquired prior to describing the structural data of the stimulation electrodes. At least one computer (5); b) An electronic data storage device (6) for storing at least the electrode template data; c) A first medical imaging device (7) configured to generate the first medical image data; d) A second medical imaging device (8) configured to generate the second digital medical image data, The at least one computer is - A first medical imaging device (7) for acquiring the first medical image data from the first medical imaging device; - A second medical imaging device (8) for acquiring the second digital medical image data from the second medical imaging device, and At least one electronic data storage device (6) for acquiring at least the electrode template data from the data storage device, A medical system (4) operably coupled to.

18. The system according to claim 17, wherein the first imaging device (7) and the second medical imaging device (8) are the same.

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