Systems and methods for performing one-key scanning through camera and

Abstract

A method for performing a scan of a subject, the method comprising: receiving a selected scenario for the scan; and upon receiving the start signal, triggering automatic marking of the subject on a diagnostic table of a magnetic resonance imaging (MRI) scanner with a three-dimensional (3D) camera. The method includes obtaining landmark localization data from a 3D camera and localizing a region of interest using the landmark localization data. The method includes triggering a calibration scan of the subject by the MRI scanner after the automatic tagging and obtaining calibration data from the MRI scanner and refining the localization of the region of interest with the calibration data. The method includes generating a geometric plan for subsequent scans using both landmark localization data and calibration data, and triggering at least one subsequent scan of the subject by the MRI scanner based on the geometric plan.

Description

Background Art

[0001] The subject matter disclosed herein relates to medical imaging, and more particularly, to systems and methods for performing one-button scanning with a magnetic resonance imaging (MRI) system through a camera and calibration integrated workflow.

[0002] Non-invasive imaging techniques allow images of internal structures or features of a patient / object to be obtained without performing an invasive procedure on the patient / object. Specifically, such non-invasive imaging techniques rely on various physical principles (such as differential transmission of X-rays through a target volume, reflection of acoustic waves within a volume, paramagnetism of different tissues and materials within a volume, decomposition of target radionuclides within the body, etc.) to acquire data and construct an image or otherwise represent the observed internal features of the patient / object.

[0003] During MRI, when a substance such as human tissue is subjected to a uniform magnetic field (polarization field B0), the individual magnetic moments of the spins in the tissue attempt to align with the polarization field, but precess around it in a random order at their characteristic Larmor frequency. If the substance or tissue is subjected to a magnetic field (excitation field B1) that is in the xy plane and close to the Larmor frequency, the net alignment moment or "longitudinal magnetization" M z can be rotated or "tilted" into the xy plane to produce a net transverse magnetic moment M t After the excitation signal B1 is terminated, a signal is emitted by the excited spins and can be received and processed to form an image.

[0004] When these signals are used to generate images, the magnetic field gradient (G x , G y and G z ). Typically, the area to be imaged is scanned by a series of measurement cycles in which these gradient fields are varied depending on the particular localization method used. The resulting set of received nuclear magnetic resonance (NMR) signals is digitized and processed to reconstruct an image using one of the well-known reconstruction techniques.

[0005] Setting up off-isocenter anatomical scans, such as musculoskeletal (MSK) MRI scans (e.g., for shoulders, biceps, limbs, wrists, knees, arms, etc.), is always a challenge and requires a skilled operator. For example, left-right positioning of a limb is always a challenging problem for MSK scans. Typically, the protocol for these scans involves obtaining and utilizing 3-plane localizers (e.g., images in the axial, sagittal, and coronal planes), which are inaccurate most of the time, resulting in the need to repeat the localizer scans to obtain the proper settings for subsequent scans. Even though obtaining the localizer images involves a simple protocol, these off-isocenter anatomical scans become long scans if the subject (e.g., patient) is not properly set up for the scan. Summary of the invention

[0006] The following shows an overview of certain embodiments disclosed herein. It should be understood that these aspects are provided only to provide the reader with a brief overview of these specific embodiments, and these aspects are not intended to limit the scope of the present disclosure. In fact, the present disclosure may cover various aspects that may not be shown below.

[0007] In one embodiment, a computer-implemented method for performing a scan of a region of interest of a subject using a magnetic resonance imaging (MRI) system is provided. The computer-implemented method includes: receiving, via a processor, a selected protocol for performing a scan of a region of interest of a subject using an MRI scanner of the MRI system. The computer-implemented method also includes: upon receiving a start signal, triggering, via the processor, automatic marking of a subject on a diagnostic table of an MRI scanner of the MRI system using a three-dimensional (3D) camera. The computer-implemented method also includes: obtaining landmark location data from the 3D camera at the processor and locating the region of interest using the landmark location data via the processor. The computer-implemented method even includes: triggering, via the processor, a calibration scan of the subject by the MRI scanner after the automatic marking. The computer-implemented method further includes: obtaining, at the processor, calibration data from the MRI scanner, and refining the location of the region of interest using the calibration data via the processor. The computer-implemented method still further includes: generating, via the processor, a geometric plan for performing a subsequent scan of the region of interest of the subject by the MRI scanner using both the landmark location data and the calibration data. The computer implemented method further includes triggering, via the processor, at least one subsequent scan of the subject by the MRI scanner based on the geometric plan.

[0008] In another embodiment, a system for performing a scan of a region of interest of a subject using a magnetic resonance imaging (MRI) system is provided. The system includes a memory encoding a processor executable routine. The system also includes a processor configured to access the memory and execute the processor executable routine, wherein the processor executable routine causes the processor to perform an action when executed by the processor. The action includes: receiving a selected scheme for performing a scan of a region of interest of a subject using an MRI scanner of the MRI system. The action also includes: upon receiving a start signal, triggering automatic marking of a subject on a diagnostic table of an MRI scanner of the MRI system using a three-dimensional (3D) camera. The action also includes: obtaining landmark positioning data from the 3D camera and positioning the region of interest using the landmark positioning data. The action even includes: after the automatic marking, triggering a calibration scan of the subject by the MRI scanner. The action further includes: obtaining calibration data from the MRI scanner, and using the calibration data to refine the positioning of the region of interest. The action further includes: generating a geometric plan for performing a subsequent scan of the region of interest of the subject by the MRI scanner using both the landmark positioning data and the calibration data. The actions further include triggering at least one subsequent scan of the subject by the MRI scanner based on the geometric plan.

[0009] In another embodiment, a non-transitory computer readable medium includes processor executable code, which when executed by a processor causes the processor to perform an action. The action includes: receiving a selected protocol for performing a scan of a subject's region of interest using an MRI scanner of a magnetic resonance imaging (MRI) system. The action also includes: upon receiving a start signal, triggering automatic marking of a subject on a diagnostic table of an MRI scanner of the MRI system using a three-dimensional (3D) camera. The action also includes: obtaining landmark location data from the 3D camera and using the landmark location data to locate the region of interest. The action even includes: after the automatic marking, triggering a calibration scan of the subject by the MRI scanner. The action further includes: obtaining calibration data from the MRI scanner, and using the calibration data to refine the location of the region of interest. The action further includes: generating a geometric plan for performing a subsequent scan of the subject's region of interest by the MRI scanner using both the landmark location data and the calibration data. The action further includes: triggering at least one subsequent scan of the subject by the MRI scanner based on the geometric plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] These and other features, aspects, and advantages of the present subject matter will be better understood when the following detailed description is read with reference to the accompanying drawings, in which like characters refer to like parts throughout the several views, and in which:

[0011] Figure 1 An embodiment of a magnetic resonance imaging (MRI) system suitable for use with the disclosed techniques is shown;

[0012] Figure 2 The present invention is shown in accordance with various aspects of the present disclosure arranged in a scanning room. Figure 1 A schematic diagram of an MRI scanner (e.g., having a camera coupled to the MRI scanner) of an MRI system in FIG.

[0013] Figure 3 The present invention is shown in accordance with various aspects of the present disclosure arranged in a scanning room. Figure 1 A schematic diagram of an MRI scanner (e.g., having a camera coupled to a ceiling) of an MRI system in FIG.

[0014] Figure 4 The present disclosure shows the use of various aspects of Figure 1 Schematic diagram of an MRI system performing one-button scanning through a camera and calibration integrated workflow;

[0015] Figure 5 A method for utilizing the Figure 1 A flowchart of a method for performing a scan of a region of interest of a subject (e.g., a patient) by an MRI system in the present invention, the MRI system utilizing a camera and calibration integrated workflow;

[0016] Figure 6 A method for utilizing the Figure 1 A flowchart of a method for performing a scan of a region of interest of a subject (e.g., a patient) by an MRI system in the present invention, the MRI system utilizing a camera and calibration integrated workflow (e.g., with a localizer and a diagnostic scan);

[0017] Figure 7 is an example of an image of a knee acquired during a calibration scan in accordance with aspects of the present disclosure;

[0018] Figure 8 is an example of an image of coil signal strength information obtained during a calibration scan of a knee in accordance with aspects of the present disclosure;

[0019] Fig. 9 is another example of an image of coil signal strength information obtained during a calibration scan of a knee in accordance with aspects of the present disclosure;

[0020] Fig.10 is an example of a locator image of a knee obtained in accordance with aspects of the present disclosure;

[0021] Fig.11is an example of a high resolution image of a knee obtained in accordance with aspects of the present disclosure; and

[0022] Fig.12 A method for utilizing the Figure 1 Flowchart of a method for performing a scan of a region of interest of a subject (eg, a patient) by an MRI system in an integrated workflow (eg, with a diagnostic scan) utilizing a camera and calibration. DETAILED DESCRIPTION

[0023] One or more specific embodiments will be described below. In order to provide a concise description of these embodiments, not all features of an actual implementation are described in the specification. It should be understood that in the development of any such actual implementation, as in any engineering or design project, many implementation-specific decisions must be made to achieve the developer's specific goals, such as complying with system-related and business-related constraints that may vary from implementation to implementation. In addition, it should be understood that such development efforts may be complex and time-consuming, but are still routine tasks for design, fabrication, and manufacturing for ordinary technicians who benefit from this disclosure.

[0024] When introducing elements of various embodiments of the present subject matter, the articles "a," "an," "the," and "said" are intended to indicate that there are one or more of the recited elements. The terms "comprising," "including," and "having" are intended to be inclusive and mean that there may be additional elements in addition to the listed elements. Furthermore, any numerical examples in the following discussion are intended to be non-limiting, and thus the appended numerical values, ranges, and percentages are within the scope of the disclosed embodiments.

[0025] Although various aspects of the following discussion are provided in the context of medical imaging, it should be understood that the technology disclosed in the present invention is not limited to such medical contexts. In fact, the examples and explanations are provided in such medical contexts only to facilitate explanation by providing examples of realistic specific implementations and applications. However, the technology disclosed in the present invention can also be used in other contexts, such as non-destructive inspection of manufactured parts or goods (i.e., quality control or quality review application scenarios) and / or image reconstruction of non-invasive inspection of packages, boxes, suitcases, etc. (i.e., security inspection or screening application scenarios). In general, the technology disclosed in the present invention can be used in any imaging or screening context or image processing or photography field, in which a group or class of collected data undergoes a reconstruction process to generate an image or volume.

[0026] The deep learning (DL) methods discussed herein may be based on artificial neural networks and may therefore encompass one or more of the following: deep neural networks, fully interconnected networks, convolutional neural networks (CNNs), unfolded neural networks, perceptrons, codecs, recurrent networks, wavelet filter banks, u-nets, generative adversarial networks (GANs), dense neural networks, or other neural network architectures. Neural networks may include shortcuts, activations, batch normalization layers, and / or other features. These techniques are referred to herein as DL techniques, but the term may also be used with particular reference to the use of deep neural networks, which are neural networks with multiple layers.

[0027] As discussed herein, DL techniques (which may also be referred to as deep machine learning, hierarchical learning, or deep structured learning) are a branch of machine learning techniques that employ mathematical representations of data and artificial neural networks for learning and processing such representations. For example, DL methods may be characterized as using one or more algorithms to extract or model highly abstract concepts of a class of data of interest. This may be accomplished using one or more processing layers, where each layer typically corresponds to a different level of abstraction, and thus may employ or utilize different aspects of the initial data or the output of the previous layer (i.e., a hierarchical or cascaded structure of layers) as the target of the process or algorithm of a given layer. In the context of image processing or reconstruction, this may be characterized as different layers corresponding to different feature levels or resolutions in the data. In general, the processing of one representation space to the next level representation space may be viewed as a "stage" of the process. Each stage of the process may be performed by a separate neural network or by different parts of a larger neural network.

[0028] The present disclosure provides a system and method for performing a one-button scan through a camera and calibration integrated workflow, for performing a scan of a region of interest of a subject (e.g., a patient) using a magnetic resonance imaging (MRI) system. Specifically, the disclosed system and method include: receiving a selected scheme for performing a scan of a region of interest of a subject using an MRI scanner of the MRI system via a processor. The disclosed system and method also include: upon receiving a start signal (e.g., a start input signal), triggering, via a processor, automatic marking of a subject on a diagnostic table of an MRI scanner of the MRI system using a three-dimensional (3D) camera. The disclosed system and method also include: obtaining landmark positioning data from the 3D camera at the processor and positioning the region of interest using the landmark positioning data via the processor. The disclosed system and method even include: after automatic marking, triggering, via the processor, a calibration scan of the subject by the MRI scanner. The disclosed system and method further include: obtaining calibration data from the MRI scanner at the processor, and refining the positioning of the region of interest using the calibration data via the processor. The disclosed systems and methods still further include: generating, via the processor, a geometric plan (and prescription parameters for image scan planes) for performing a subsequent scan of a region of interest of a subject via the MRI scanner using both the landmark positioning data and the calibration data. The disclosed systems and methods still further include: triggering, via the processor, at least one subsequent scan of the subject via the MRI scanner based on the geometric plan (and prescription parameters for the image scan planes).

[0029] In some embodiments, the scan is a non-isocentric anatomical scan of the subject. For example, the scan can be a musculoskeletal MRI scan of the shoulder, biceps, limbs, wrist, knee, arm, or other anatomical region. In some embodiments, at least one subsequent scan is a localizer scan (e.g., for a selected scan protocol) to obtain a localizer image. In some embodiments, at least one subsequent scan is a diagnostic scan (e.g., using a selected scan protocol) to obtain a diagnostic image.

[0030] In certain embodiments, landmark location data comprises one or more of the following: subject position, subject orientation, subject's body contour, subject's surface level sub-region key point, upper / lower coverage, right / left coverage, depth, the positioning of coil and the positioning of blanket. In certain embodiments, calibration data comprises one or more of the following: left / right center, front / back center, offset information from coil signal strength information, patient size and anatomical structure specific fine positioning. In certain embodiments, landmark location data is used for the positioning of region of interest comprises landmark location data is used for the upper / lower positioning of region of interest, and wherein calibration data is used for both front / back positioning and right / left positioning of region of interest. Calibration scanning also enables detection and determination of implants in region of interest.

[0031] In certain embodiments, the disclosed systems and methods include: when an abnormal subject condition is detected based on the landmark positioning data, providing a subject perceptible command (e.g., a voice command via a speaker) via a processor to adjust the positioning before triggering the calibration scan. In certain embodiments, the disclosed systems and methods include providing a user perceptible warning (e.g., on a display on an operator console of the MRI system) via a processor that an abnormal subject condition is detected based on the landmark positioning data, thereby excluding the intelligent prescription module (e.g., AIR from General Electric Healthcare) x TM ), the smart prescription module uses deep learning algorithms to automatically identify anatomical structures and specify slices for diagnostic scans.

[0032] Considering the above, Figure 1 , a magnetic resonance imaging (MRI) system 100 is schematically shown as including a scanner 102, a scanner control circuit 104, and a system control circuit 106. According to the embodiments described herein, the MRI system 100 is generally configured to perform MR imaging. It should be noted that the techniques described herein can also be used with an imaging system having a dual imaging modality (e.g., a computed tomography (CT) / MRI system or a positron emission tomography (PET) / MRI system).

[0033] The system 100 also includes a remote access and storage system or device, such as a picture archiving and communication system (PACS) 108, or other devices, such as remote radiation equipment, that enable on-site or off-site access to data acquired by the system 100. In this way, MR data can be acquired and then processed and evaluated on-site or off-site. Although the MRI system 100 can include any suitable scanner or detector, in the illustrated embodiment, the system 100 includes a whole body scanner 102 having a housing 120 through which an aperture 122 is formed. A diagnostic table 124 can be moved into the aperture 122 to allow a patient 126 (e.g., a subject) to be positioned therein to image selected anatomical structures within the patient's body.

[0034] The scanner 102 includes a series of associated coils for generating a controlled magnetic field for exciting gyromagnetic materials within the anatomical structure of the patient being imaged. Specifically, a main magnet coil 128 is provided for generating a main magnetic field B0 that is generally aligned with the orifice 122. A series of gradient coils 130, 132, and 134 allow the generation of controlled gradient magnetic fields during the examination sequence for position encoding of certain gyromagnetic nuclei in the patient 126. A radio frequency (RF) coil 136 (e.g., an RF transmit coil) is configured to generate radio frequency pulses for exciting certain gyromagnetic nuclei in the patient. In addition to the coils that may be located locally in the scanner 102, the system 100 also includes a set of receiving coils or RF receiving coils 138 (e.g., a coil array) configured to be placed proximal to the patient 126 (e.g., against the patient). For example, the receiving coil 138 may include a cervical / thoracic / lumbar (CTL) coil, a head coil, a single-sided spine coil, etc. Generally, receive coil 138 is placed near or above patient 126 to receive the weak RF signals (relative to the transmit pulses generated by the scanner coil) generated by certain gyromagnetic nuclei in the patient's body as patient 126 returns to his or her relaxed state.

[0035] The various coils of the system 100 are controlled by external circuits to generate the required fields and pulses and read the emission from the gyromagnetic material in a controlled manner. In the illustrated embodiment, the main power supply 140 provides power to the primary field coil 128 to generate the primary magnetic field Bo. The power input (e.g., power from a utility or grid), a power distribution unit (PDU), a power supply (PS), and a driver circuit 150 can provide power together to pulse the gradient field coils 130, 132, and 134. The driver circuit 150 may include amplification and control circuits for supplying current to the coils as defined by the digitized pulse sequence output by the scanner control circuit 104.

[0036] Another control circuit 152 is provided for regulating the operation of the RF coil 136. The circuit 152 includes a switching device for alternating between an active mode of operation and a passive mode of operation, wherein the RF coil 136 transmits and does not transmit a signal, respectively. The circuit 152 also includes an amplification circuit configured to generate RF pulses. Similarly, the receiving coil 138 is connected to a switch 154, which is capable of switching the receiving coil 138 between a receiving mode and a non-receiving mode. Thus, in the receiving mode, the receiving coil 138 resonates with the RF signal generated by the release of the gyromagnetic nuclei in the patient 126, and in the non-receiving mode, they do not resonate with the RF energy from the transmitting coil (i.e., the coil 136) to prevent unintended operation. In addition, the receiving circuit 156 is configured to receive data detected by the receiving coil 138, and may include one or more multiplexing and / or amplification circuits.

[0037] It should be noted that although the scanner 102 and control / amplification circuits described above are shown as being coupled by a single line, in actual examples there may be many such lines. For example, separate lines may be used for control, data communication, power transmission, etc. In addition, appropriate hardware may be provided along each type of line for properly processing data and current / voltage. In practice, various filters, digitizers, and processors may be provided between the scanner and either or both of the scanner control circuit 104 and the system control circuit 106.

[0038] As shown, the scanner control circuit 104 includes an interface circuit 158 ​​that outputs signals for driving the gradient field coils and the RF coils and for receiving data representing magnetic resonance signals generated in the examination sequence. The interface circuit 158 ​​is coupled to a control and analysis circuit 160. Based on a defined scheme selected via the system control circuit 106, the control and analysis circuit 160 executes commands for driving the circuits 150 and 152.

[0039] The control and analysis circuitry 160 is also used to receive magnetic resonance signals and perform subsequent processing before transmitting the data to the system control circuitry 106. The scanner control circuitry 104 also includes one or more memory circuits 162 that store configuration parameters, pulse sequence descriptions, examination results, etc. during operation.

[0040] Interface circuit 164 is coupled to control and analysis circuit 160 for exchanging data between scanner control circuit 104 and system control circuit 106. In some embodiments, control and analysis circuit 160, although shown as a single unit, may include one or more hardware devices. System control circuit 106 includes interface circuit 166 that receives data from scanner control circuit 104 and transmits data and commands back to scanner control circuit 104. Control and analysis circuit 168 may include a CPU in a general or special purpose computer or workstation. Control and analysis circuit 168 is coupled to memory circuit 170 to store programming code for operating MRI system 100, and to store processed image data for later reconstruction, display and transmission. The programming code may execute one or more algorithms that are configured to perform reconstruction of acquisition data as described below when executed by a processor. In some embodiments, memory circuit 170 may store one or more neural networks for reconstruction of acquisition data as described below. In some embodiments, image reconstruction may occur on a separate computing device having processing circuits and memory circuits.

[0041] The programming code may enable a one-button scan to be performed through a camera and calibration integrated workflow for performing a scan of a region of interest of a subject 126 (e.g., a patient) using the MRI system 100. Specifically, the programming code may enable receiving a selected protocol for performing a scan of a region of interest of a subject 126 using an MRI scanner 102 of the MRI system 100. The programming code may enable triggering automatic marking of a subject on a diagnostic table of an MRI scanner 102 of the MRI system 100 using a three-dimensional (3D) camera upon receiving a start signal (e.g., a start input signal). The programming code may enable obtaining landmark positioning data from the 3D camera and positioning a region of interest using the landmark positioning data. The programming code may enable triggering a calibration scan of the subject 126 by the MRI scanner 102 after automatic marking. The programming code may enable obtaining calibration data from the MRI scanner 102 and using the calibration data to refine the positioning of the region of interest. The programming code may enable generation of a geometric plan (and prescription parameters for the image scan planes) for performing a subsequent scan of a region of interest of a subject by the MRI scanner utilizing both the landmark positioning data and the calibration data. The programming code may enable triggering of at least one subsequent scan of the subject by the MRI scanner based on the geometric plan (and prescription parameters for the image scan planes).

[0042] In some embodiments, the scan is a non-isocentric anatomical scan of the subject. For example, the scan can be a musculoskeletal MRI scan of the shoulder, biceps, limbs, wrist, knee, arm, or other anatomical region. In some embodiments, at least one subsequent scan is a localizer scan (e.g., for a selected scan protocol) to obtain a localizer image. In some embodiments, at least one subsequent scan is a diagnostic scan (e.g., using a selected scan protocol) to obtain a diagnostic image.

[0043] In certain embodiments, landmark location data comprises one or more of the following: subject position, subject orientation, subject's body contour, subject's surface level sub-region key point, upper / lower coverage, right / left coverage, depth, the positioning of coil and the positioning of blanket. In certain embodiments, calibration data comprises one or more of the following: left / right center, front / back center, offset information from coil signal strength information, patient size and anatomical structure specific fine positioning. In certain embodiments, landmark location data is used for the positioning of region of interest comprises landmark location data is used for the upper / lower positioning of region of interest, and wherein calibration data is used for both front / back positioning and right / left positioning of region of interest. Calibration scanning also enables detection and determination of implants in region of interest.

[0044] In some embodiments, the programming code can enable, upon detection of an abnormal subject condition based on the landmark positioning data, providing, via the processor, a subject perceptible command (e.g., a voice command via a speaker) to adjust positioning prior to triggering a calibration scan. In some embodiments, the programming code can enable providing a user perceptible warning (e.g., on a display on an operator console of the MRI system) that an abnormal subject condition is detected based on the landmark positioning data, thereby excluding an intelligent prescription module (e.g., AIR from GE Healthcare) from the MRI system. x TM ), the smart prescription module uses deep learning algorithms to automatically identify anatomical structures and specify slices for diagnostic scans.

[0045] Additional interface circuitry 172 may be provided for exchanging image data, configuration parameters, etc. with external system components such as remote access and storage device 108. Finally, system control and analysis circuitry 168 may be communicatively coupled to various peripheral devices for facilitating operator interface and generating hard copies of reconstructed images. In the illustrated embodiment, these peripheral devices include a printer 174, a monitor 176, and a user interface 178, which may include devices such as a keyboard, a mouse, a touch screen (e.g., integrated with monitor 176), etc.

[0046] The MRI imaging system 100 also includes an optical imaging system 180. The optical imaging system 180 includes one or more cameras 182 (e.g., 3D cameras) coupled to the MRI scanner 102 or separately disposed in a scanning room with the MRI scanner 102. The one or more cameras 182 are configured to capture 3D optical imaging data of a subject 126 placed on a diagnostic table 124 before being moved into the bore 122 of the MRI scanner 102 for any subsequent scans (e.g., calibration scans, localizer scans, diagnostic scans, etc.). In the techniques described herein, the 3D optical imaging data is used as landmark positioning data. The optical imaging system 180 communicates with the control and analysis circuit 160 and / or the control and analysis circuit 168 via respective interfaces 164, 166.

[0047] Figure 2 and Figure 3 The optical imaging system 180 is provided in the scanning room 184. Figure 1 Schematic diagram of an MRI scanner 102 of an MRI system 100 in FIG. Figure 2 As depicted in FIG. 1 , a camera 182 (e.g., a 3D camera) of an optical imaging system 180 is coupled to the MRI scanner 102 via an extension 186 that positions the camera 182 above a subject 126 on a diagnostic table 124 outside of the bore 122 of the MRI scanner 102. Figure 3 As shown, the camera 182 is separate from the MRI scanner 102. Specifically, the camera 182 of the optical imaging system 180 is coupled to the ceiling 188 of the scanning room 184 via an extension 190 that positions the camera 182 above the subject 126 on the diagnostic table 124 outside the bore 122 of the MRI scanner 102.

[0048] Figure 4 Shows the use of Figure 1 Schematic diagram of the MRI system 100 in performing a one-button scan through a camera and calibration integrated workflow 192. The integrated workflow 192 includes obtaining a scan plan for imaging a region of interest of a subject (e.g., a patient). The region of interest to be scanned can be obtained from an electronic medical record. In certain embodiments, the scan plan can be used for non-isocentric anatomical scans, such as musculoskeletal MRI scans of shoulders, biceps, limbs, wrists, knees, arms, or other anatomical regions. As indicated by the reference numeral 194, while the scan plan is set, the subject is placed on a diagnostic table outside the bore of the MRI scanner for imaging.

[0049] Upon providing an input signal (e.g., from an operator via an operator console or automatic input from a scanning room door closing when the operator leaves the scanning room), the integrated workflow 192 includes initiating and utilizing camera-based settings (e.g., Figure 1 180) to perform automatic marking (e.g., positioning) of the subject on the diagnostic table of the MRI scanner prior to entering the bore, as indicated by reference numeral 196. The 3D camera can acquire landmark positioning data for positioning of the region of interest based on the selected scanning scheme. The landmark positioning data includes one or more of the following: subject position, subject orientation, subject body contour, surface level sub-region key points of the subject, upper / lower coverage, right / left coverage, depth, positioning of the coil, and positioning of the blanket. Camera-based settings during automatic marking may cause warnings about abnormal patient conditions (e.g., flexed knees), which may hinder the use of smart prescription modules (e.g., AIR 200 from GE Healthcare) to detect and identify abnormal patient conditions. x TM ). In some embodiments, a camera-based setup can provide commands to the subject (e.g., via voice commands via a speaker) during automatic labeling to adjust positioning. Camera-based systems provide information about the superior / inferior position of anatomy or regions of interest (e.g., based on a model), but cannot reliably detect right / left offsets of intended target anatomy for limb situations. Additionally, camera-based systems cannot reliably detect anterior / posterior offsets for spine / pelvis situations.

[0050] After automatic marking, the integrated workflow 192 also includes (as part of a continuous and integrated workflow in response to a start input signal) moving the patient into the bore of the MRI scanner via the diagnostic table and performing a pre-scan calibration. The pre-scan calibration is used to obtain calibration data for refining the positioning of the region of interest of the subject to be scanned. The calibration data includes one or more of the following: left / right center, front / back center, offset information from coil signal strength information, patient size, and anatomical structure-specific fine positioning. The calibration data can provide better right / left and front / back information from the body, which can be combined with landmark positioning data. For example, the right / left information from the calibration data can be used for limb situations, and the front / back information can be used for spine / pelvic situations. In certain embodiments, using landmark positioning data for positioning of the region of interest includes using landmark positioning data for the upper / lower positioning of the region of interest, and wherein the calibration data is used for both the front / back positioning and / or right / left positioning of the region of interest.

[0051] After the pre-scan calibration, the integrated workflow 192 even includes generating a geometric plan (and prescription parameters for image scan planes) for performing subsequent scans of the subject's region of interest by the MRI scanner using both the landmark positioning data and the calibration data, as indicated by reference numeral 200. The geometric plan specifies the slices for the subsequent scans. The geometric plan includes geometric information, such as the center, orientation, and extent of the region of interest to be scanned. In some embodiments, the first subsequent scan can be a localizer scan (e.g., a series of images (e.g., two-dimensional (2D) images) in the axial plane, the sagittal plane, and the coronal plane (e.g., a 3-plane localizer scan)) to obtain a locator image. In some embodiments, the first subsequent scan can be a high-resolution diagnostic scan. The diagnostic scan has a higher resolution than a reconnaissance or localizer scan. In some embodiments, the subsequent steps may include a localizer scan followed by a high-resolution scan. In some embodiments, a smart prescription module (e.g., AIR® from GE Healthcare) can be used before the high-resolution diagnostic scan. x TM ) (and using the localizer images) to further refine the geometric plan of the slices and the prescription. In certain embodiments, during certain abnormal subject conditions (eg, knee flexion), the smart prescription module may not be used.

[0052] Figure 5 Shown for use Figure 1 Flowchart of method 202 for performing a scan of a region of interest of a subject (eg, a patient) using an MRI system 100 in an MRI system utilizing a camera and calibration integrated workflow. One or more steps of method 202 may be performed by Figure 1 One or more of the steps of method 202 may be performed simultaneously or in parallel. Figure 5 The depicted sequence may be performed in a different order. Additionally, the method 202 may also be used with a dual imaging modality system such as a CT / MRI system or a PET / MRI system.

[0053] Before the method 202 begins, a technician places the patient to be imaged in an MRI scanner (e.g., Figure 1102). The method 202 includes receiving or obtaining a selected protocol (e.g., a scan protocol) for performing a scan of a region of interest of a subject using an MRI scanner of the MRI system (box 204). In some embodiments, the scan and scan protocol can be used for non-isocentric anatomical scans, such as musculoskeletal MRI scans of shoulders, biceps, limbs, wrists, knees, arms, or other anatomical regions. The method 202 also includes receiving a start signal (e.g., a start input signal) (box 206). The start signal can be received via input from a technician (e.g., via input provided by an operator console of the MRI system). The start signal can be automatically received when the door of the scan room is closed when the technician leaves the scan room for scanning.

[0054] The method 202 also includes triggering (eg, automatically triggering) utilizing (eg, Figure 1 180) of the optical imaging system 180 of the MRI system for automatic marking of a subject on a diagnostic table of an MRI scanner of the MRI system (e.g., based on a selected scanning protocol) (block 208). The camera-based automatic marking occurs outside the bore of the MRI scanner. The method 202 even further includes obtaining landmark location data from the 3D camera and using the landmark location data to locate a region of interest (block 210). In some embodiments, the landmark location data includes one or more of the following: subject position, subject orientation, subject body contour, subject surface level sub-region key points, top / bottom coverage, right / left coverage, depth, positioning of coils, and positioning of blankets.

[0055] The method 202 further includes: after the automatic marking, moving the subject (via the diagnostic table) into the bore of the MRI scanner (box 212). The method 202 further includes: triggering (e.g., automatically triggering) a calibration scan of the subject by the MRI scanner (e.g., based on the selected scanning scheme) (box 214). The method 202 also includes: obtaining calibration data from the MRI scanner, and using the calibration data to refine the positioning of the region of interest (box 216). The calibration data includes one or more of the following: left / right center, front / back center, offset information from coil signal strength information, patient size, and anatomical structure-specific fine positioning. The calibration data can provide better right / left and front / back information from the body, which can be combined with the landmark positioning data. For example, the right / left information from the calibration data can be used for limb situations, and the front / back information can be used for spine / pelvic situations. In certain embodiments, using the landmark location data for location of the region of interest comprises using the landmark location data for up / down location of the region of interest, and wherein the calibration data is used for both front / back location and / or right / left location of the region of interest.

[0056] The method 202 still further includes: generating a geometric plan (and prescription parameters for image scan planes) for performing subsequent scans of a region of interest of a subject by an MRI scanner using both the landmark positioning data and the calibration data (box 218). The geometric plan specifies slices for subsequent scans. The geometric plan includes geometric information, such as the center, orientation, and extent of the region of interest to be scanned. The method 202 further includes: triggering (e.g., automatically triggering) at least one subsequent scan of the subject by an MRI scanner based on the geometric plan (and prescription parameters for the image scan planes) (e.g., based on a selected scan protocol) (box 220). In some embodiments, at least one subsequent scan is a localizer scan (e.g., a series of images (e.g., 2D images) in an axial plane, a sagittal plane, and a coronal plane (e.g., a 3-plane localizer scan)) to obtain a localizer image. In some embodiments, at least one subsequent scan is a high-resolution diagnostic scan. A diagnostic scan has a higher resolution than a scout or localizer scan.

[0057] Figure 6 Shown for use Figure 1 Flowchart of method 222 for performing a scan of a region of interest of a subject (e.g., a patient) using an MRI system 100 in an MRI system utilizing a camera and calibration integrated workflow (e.g., with a localizer and diagnostic scan). One or more steps of method 222 may be performed by Figure 1 One or more of the steps of method 222 may be performed simultaneously or in parallel. Figure 6 The depicted sequence is performed in a different order. Additionally, the method 222 may also be used with a dual imaging modality system such as a CT / MRI system or a PET / MRI system.

[0058] Prior to the start of method 222, a technician places the patient to be imaged in an MRI scanner (e.g., Figure 1 102 in the MRI scanner 102 of the MRI system). Method 222 includes receiving or obtaining a selected protocol (e.g., a scan protocol) for performing a scan of a region of interest of a subject using the MRI scanner of the MRI system (box 224). In some embodiments, the scan and the scan protocol can be used for non-isocentric anatomical scans, such as musculoskeletal MRI scans of shoulders, biceps, limbs, wrists, knees, arms, or other anatomical regions. Method 222 also includes receiving a start signal (e.g., a start input signal) (box 226). The start signal can be received via input from a technician (e.g., via input provided by an operator console of the MRI system). The start signal can be automatically received when the door of the scan room is closed when the technician leaves the scan room for scanning.

[0059] The method 222 also includes triggering (eg, automatically triggering) utilizing (eg, Figure 1 180) of the optical imaging system 180 of the MRI system for automatic marking of a subject on a diagnostic table of an MRI scanner of the MRI system (e.g., based on a selected scanning protocol) (block 228). The camera-based automatic marking occurs outside the bore of the MRI scanner. The method 222 even further includes obtaining landmark location data from the 3D camera and using the landmark location data to locate a region of interest (block 230). In some embodiments, the landmark location data includes one or more of the following: subject position, subject orientation, subject body contour, subject surface level sub-region key points, top / bottom coverage, right / left coverage, depth, positioning of the coil, and positioning of the blanket.

[0060] In certain embodiments, the method 222 includes analyzing the landmark positioning data for potential abnormal patient conditions (e.g., knee flexion) (box 234). If an abnormal patient condition is detected, the method 222 includes providing a command perceptible to the subject (e.g., a voice command via a speaker) to adjust the positioning before triggering the calibration scan (box 236). If no abnormal patient condition is detected, the method 222 includes: after automatic marking, moving the subject (via the diagnostic table) into the bore of the MRI scanner (box 238).

[0061] The method 222 further includes triggering (e.g., automatically triggering) a calibration scan of the subject (e.g., based on the selected scan protocol) by the MRI scanner (box 240). The method 222 also includes obtaining calibration data from the MRI scanner and using the calibration data to refine the positioning of the region of interest (box 242). Figure 7 is an example of an image 244 of a knee acquired during a calibration scan. Figure 8 and Fig. 9 246 and 248 are examples of coil signal strength information obtained during a calibration scan of a knee. The coil signal strength information may be used to determine or update a right / left offset of a region of interest (eg, a knee). Return to Figure 6, the calibration data includes one or more of the following: left / right center, front / back center, offset information from coil signal strength information, patient size, and anatomical structure-specific fine positioning. The calibration scan also enables detection and determination of implants in the region of interest. The calibration data can provide better right / left and front / back information from the body, which can be combined with landmark positioning data. For example, the right / left information from the calibration data can be used for limb situations, and the front / back information can be used for spine / pelvic situations. In certain embodiments, using landmark positioning data for positioning of the region of interest includes using landmark positioning data for upper / lower positioning of the region of interest, and wherein the calibration data is used for both front / back positioning and / or right / left positioning of the region of interest.

[0062] The method 222 still further includes generating a geometric plan (and prescription parameters for image scanning planes) for performing subsequent scans of a region of interest of a subject by an MRI scanner using both the landmark positioning data and the calibration data (box 250). The geometric plan specifies slices for subsequent scans. The geometric plan includes geometric information, such as the center, orientation, and extent of the region of interest to be scanned. The method 222 still further includes triggering (e.g., automatically triggering) a localizer scan (e.g., a 3-plane localizer scan) by the MRI scanner based on the geometric plan (and prescription parameters for the image scanning planes) (box 252). The method 222 also includes obtaining localizer data from the localizer scan (box 254). The method 222 also includes reconstructing a localizer image from the localizer data (box 256). The localizer image is a series of images in the axial plane, the sagittal plane, and the coronal plane. For example, Fig.10 An example of localizer images 258, 260, and 262 of a knee obtained during a localizer scan is depicted. Specifically, localizer image 258 is an axial image of the knee. Localizer image 260 is a coronal image of the knee. Localizer image 262 is a sagittal image of the knee. As depicted, localizer images 258, 260, and 262 are properly centered. For example, an artificial intelligence model (e.g., a trained deep learning based model) can be used to calculate the center of a region of interest (e.g., a knee) based on landmark positioning data and calibration data when generating a geometric plan for a localizer scan.

[0063] Back to Figure 6 In some embodiments, method 222 includes generating an updated geometric plan for the diagnostic scan (and prescription parameters for the image scan planes) based on the localizer image (block 264). In some embodiments, a deep learning algorithm can be utilized to automatically identify anatomical structures in the localizer image and prescribe slices for the diagnostic scan. For example, smart prescriptions (e.g., AIR x TM) can be used to generate a geometric plan. In certain embodiments, statistical learning can be used to automatically identify anatomical structures in the localizer image and prescribe slices for diagnostic scans.

[0064] The method 222 includes triggering (e.g., automatically triggering) a diagnostic scan based on the updated geometric plan (and prescription parameters for the image scan planes) (block 266). The diagnostic scan has a higher resolution than the scout or localizer scans. The method 222 also includes reconstructing one or more high-resolution diagnostic images based on the image data from the diagnostic scan (block 268). Fig.11 Depicted are examples of high resolution diagnostic images 270, 272, 274 of a knee obtained during a diagnostic scan. Specifically, diagnostic image 270 is an axial image of the knee. Diagnostic image 272 is a coronal image of the knee. Diagnostic image 272 is a sagittal image of the knee.

[0065] Fig.12 Shown for use Figure 1 Flowchart of method 276 for performing a scan of a region of interest of a subject (e.g., a patient) using an MRI system 100 in an integrated workflow (e.g., with a diagnostic scan) using a camera and calibration. One or more steps of method 276 may be performed by Figure 1 One or more of the steps of method 276 may be performed simultaneously or in parallel. Fig.12 The depicted sequence may be performed in a different order. Additionally, the method 276 may also be used with a dual imaging modality system such as a CT / MRI system or a PET / MRI system.

[0066] Prior to the start of method 276, a technician places the patient to be imaged in an MRI scanner (e.g., Figure 1 276 includes receiving or obtaining a selected protocol (e.g., a scan protocol) for performing a scan of a region of interest of a subject using an MRI scanner of the MRI system (box 278). In some embodiments, the scan and scan protocol can be used for non-isocentric anatomical scans, such as musculoskeletal MRI scans of shoulders, biceps, limbs, wrists, knees, arms, or other anatomical regions. Method 276 also includes receiving a start signal (e.g., a start input signal) (box 280). The start signal can be received via input from a technician (e.g., via input provided by an operator console of the MRI system). The start signal can be automatically received when the door of the scan room is closed when the technician leaves the scan room for scanning.

[0067] The method 276 also includes triggering (eg, automatically triggering) utilizing (eg, Figure 1180) of the optical imaging system 180 of the MRI system for automatic marking of a subject on a diagnostic table of an MRI scanner of the MRI system (e.g., based on a selected scanning protocol) (block 282). The camera-based automatic marking occurs outside the bore of the MRI scanner. The method 276 even further includes obtaining landmark location data from the 3D camera and using the landmark location data to locate a region of interest (block 284). In some embodiments, the landmark location data includes one or more of the following: subject position, subject orientation, subject body contour, subject surface level sub-region key points, top / bottom coverage, right / left coverage, depth, positioning of the coil, and positioning of the blanket.

[0068] In certain embodiments, the method 276 includes analyzing the landmark location data for a potential abnormal patient condition (e.g., knee flexion) (block 286). If an abnormal patient condition is detected, the method 276 includes providing a user-perceivable warning (e.g., on a display on an operator console of the MRI system) that an abnormal patient condition has been detected based on the landmark location data, thereby excluding a smart prescription module (e.g., AIR from GE Healthcare). x TM ) is utilized (box 288). If no abnormal patient condition is detected or after a warning is provided, method 276 includes: after automatic marking, moving the subject (via the diagnostic table) into the bore of the MRI scanner (box 290).

[0069] Method 276 further includes: triggering (e.g., automatically triggering) a calibration scan of the subject (e.g., based on the selected scanning scheme) by the MRI scanner (frame 292). Method 276 also includes: obtaining calibration data from the MRI scanner, and using the calibration data to refine the positioning of the region of interest (frame 294). The calibration data includes one or more of the following: left / right center, front / back center, offset information from coil signal strength information, patient size, and anatomical structure-specific fine positioning. The calibration scan also enables detection and determination of implants in the region of interest. The calibration data can provide better right / left and front / back information from the body, which can be combined with landmark positioning data. For example, the right / left information from the calibration data can be used for limb situations, and the front / back information can be used for spine / pelvic situations. In certain embodiments, using landmark positioning data for positioning of the region of interest includes using landmark positioning data for upper / lower positioning of the region of interest, and wherein the calibration data is used for both front / back positioning and / or right / left positioning of the region of interest.

[0070] The method 276 still further includes generating a geometric plan (and prescription parameters for image scan planes) for performing subsequent scans of the subject's region of interest by the MRI scanner using both the landmark positioning data and the calibration data (block 296). The geometric plan specifies the slices for the subsequent scans. The geometric plan includes geometric information such as the center, orientation, and extent of the region of interest to be scanned.

[0071] The method 276 includes triggering (e.g., automatically triggering) a diagnostic scan based on the geometric plan (and the prescription parameters for the image scan planes) (block 298). The method 276 performs the diagnostic scan without a localizer scan. The method 276 also includes reconstructing one or more high-resolution diagnostic images based on the image data from the diagnostic scan (block 300).

[0072] The technical effects of the disclosed subject matter include providing a one-click scan performed by a camera and calibration integrated workflow for performing a scan of a region of interest of a subject (e.g., a patient) using an MRI system. Specifically, the disclosed subject matter combines camera-based surface patient positioning with in vivo anatomical landmark-based refinement of a calibration scan to obtain a customized locator or high-resolution scan in the first stage after patient setup. Specifically, camera-based automatic marking and intelligent prescriptions provide surface-level dynamic anatomical structure detection, upper / lower coverage, right / left coverage, patient position and patient information, as well as information about blankets, coils, and depth information. The calibration scan provides accurate positioning of right / left and front / back centers and offsets, coil sensitivity, orientation of accurate anatomical landmarks, and the ability to detect and determine implants. The technical effects of the disclosed subject matter also include providing shorter scan times (especially for anatomical scans that deviate from the isocenter, such as MSK scans). The technical effects of the disclosed subject matter also include providing more accurate setup and prescriptions.

[0073] The technology presented and claimed herein is referred to and applied to physical and specific examples of a practical nature that clearly improves upon the present state of the art and, therefore, is not abstract, intangible, or purely theoretical. In addition, if any claim appended to the end of this specification contains one or more elements designated as "means for [performing] the function of" or "steps for [performing] the function of," it is intended that such elements be interpreted under 35 USC § 112(f). However, for any claim containing elements designated in any other manner, it is not intended that such elements be interpreted under 35 USC § 112(f).

[0074] This written description uses examples to disclose the subject matter, including the best mode, and also to enable those skilled in the art to practice the subject matter, including making and using any devices or systems and performing any included methods. The patentable scope of the subject matter is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insignificant differences from the literal language of the claims.

Claims

1. A computer-implemented method for performing a scan of a region of interest of a subject using a magnetic resonance imaging (MRI) system, the method comprising: receiving, via a processor, a selected protocol for performing the scanning of the region of interest of the subject using an MRI scanner of the MRI system; upon receiving a start signal, triggering, via the processor, automatic marking of the subject on a diagnostic table of the MRI scanner of the MRI system using a three-dimensional (3D) camera; obtaining, at the processor, landmark location data from the 3D camera and locating the region of interest using the landmark location data via the processor; triggering, via the processor, a calibration scan of the subject by the MRI scanner after the automatic marking; obtaining, at the processor, calibration data from the MRI scanner, and utilizing, via the processor, the calibration data to refine the positioning of the region of interest; generating, via the processor, a geometric plan for performing a subsequent scan of the region of interest of the subject with the MRI scanner utilizing both the landmark location data and the calibration data; as well as At least one subsequent scan of the subject by the MRI scanner is triggered via the processor based on the geometric plan. 2 . The computer-implemented method of claim 1 , wherein the scan comprises an off-isocentric anatomical scan of the subject.

3. The computer-implemented method of claim 2, wherein the at least one subsequent scan comprises a localizer scan to obtain a localizer image.

4. The computer-implemented method of claim 2, wherein the at least one subsequent scan comprises a diagnostic scan to obtain diagnostic images.

5. A computer-implemented method according to claim 1, wherein the landmark positioning data includes one or more of the following: subject position, subject orientation, body contour of the subject, surface level sub-region key points of the subject, top / bottom coverage, right / left coverage, depth, positioning of the coil, and positioning of the blanket.

6. The computer-implemented method of claim 5, wherein the calibration data includes one or more of: left / right center, anterior / posterior center, offset information from coil signal strength information, patient size, and anatomical structure specific fine positioning.

7. A computer-implemented method according to claim 1, wherein using the landmark positioning data for positioning the region of interest includes using the landmark positioning data for upper / lower positioning of the region of interest, and wherein using the calibration data for both front / back positioning and right / left positioning of the region of interest.

8. The computer-implemented method of claim 1 , further comprising: When an abnormal subject condition is detected based on the landmark positioning data, a subject perceptible command is provided via the processor to adjust positioning prior to triggering the calibration scan.

9. The computer-implemented method of claim 1 , further comprising: A user-perceptible alert is provided, via the processor, that an abnormal patient condition is detected based on the landmark location data, thereby precluding utilization of a smart prescription module.

10. A system for performing a scan of a region of interest of a subject using a magnetic resonance imaging (MRI) system, the system comprising: a memory encoding a processor-executable routine; and a processor configured to access the memory and execute the processor-executable routine, wherein the processor-executable routine, when executed by the processor, causes the processor to: receiving a selected protocol for performing the scanning of the region of interest of the subject using an MRI scanner of the MRI system; upon receiving a start signal, triggering automatic marking of the subject on a diagnostic table of the MRI scanner of the MRI system using a three-dimensional (3D) camera; Obtaining landmark location data from the 3D camera and locating the region of interest using the landmark location data; triggering a calibration scan of the subject by the MRI scanner after the automatic marking; obtaining calibration data from the MRI scanner and utilizing the calibration data to refine the positioning of the region of interest; generating a geometric plan for performing a subsequent scan of the region of interest of the subject with the MRI scanner using both the landmark location data and the calibration data; as well as At least one subsequent scan of the subject by the MRI scanner is triggered based on the geometric plan.

11. The system of claim 10, wherein the scan comprises an off-isocentric anatomical scan of the subject.

12. The system of claim 11, wherein the at least one subsequent scan comprises a localizer scan to obtain a localizer image.

13. The system of claim 11, wherein the at least one subsequent scan comprises a diagnostic scan to obtain diagnostic images.

14. The system of claim 10, wherein the landmark location data comprises one or more of: subject position, subject orientation, body contour of the subject, surface level sub-region key points of the subject, top / bottom coverage, right / left coverage, depth, positioning of coils, and positioning of blankets.

15. The system of claim 14, wherein the calibration data includes one or more of: left / right center, anterior / posterior center, offset information from coil signal strength information, patient size, and anatomical structure specific fine positioning.

16. The system of claim 10, wherein using the landmark location data for location of the region of interest comprises using the landmark location data for up / down location of the region of interest, and wherein using the calibration data for both front / back location and right / left location of the region of interest.

17. The system of claim 10, wherein the processor-executable routine, when executed by the processor, further causes the processor to provide a subject-perceptible command to adjust positioning prior to triggering the calibration scan when an abnormal subject condition is detected based on the landmark positioning data.

18. The system of claim 10, wherein the processor-executable routine, when executed by the processor, further causes the processor to provide a user-perceivable alert that an abnormal patient condition is detected based on the landmark location data, thereby precluding utilization of a smart prescription module.

19. A non-transitory computer readable medium comprising processor executable code which, when executed by a processor, causes the processor to: receiving a selected protocol for performing a scan of a region of interest of a subject using a magnetic resonance imaging (MRI) scanner of the MRI system; upon receiving a start signal, triggering automatic marking of the subject on a diagnostic table of the MRI scanner of the MRI system using a three-dimensional (3D) camera; Obtaining landmark location data from the 3D camera and locating the region of interest using the landmark location data; triggering a calibration scan of the subject by the MRI scanner after the automatic marking; obtaining calibration data from the MRI scanner and utilizing the calibration data to refine the positioning of the region of interest; generating a geometric plan for performing a subsequent scan of the region of interest of the subject with the MRI scanner using both the landmark location data and the calibration data; as well as At least one subsequent scan of the subject by the MRI scanner is triggered based on the geometric plan.

20. The non-transitory computer-readable medium of claim 19, wherein using the landmark positioning data for positioning the region of interest comprises using the landmark positioning data for up / down positioning of the region of interest, and wherein using the calibration data for both front / back positioning and right / left positioning of the region of interest.

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