Abstract: A system (102) includes a digital information repository (106) configured to store information about performances of individuals, including performances of an individual of interest. The system further includes a computing apparatus (103). The computing apparatus includes a memory (110) configured to store instructions for a performance benchmarking engine trained to learn factors of the performances that impact key performance indicators independent of the individuals’ performance. The computing apparatus further includes a processor (108) configured execute the stored instructions for the performance benchmarking engine to determine a key performance indicator of interest for the individual of interest based at least in part on the information in the digital information repository about the performances of the individual of interest and the learned factors that impact the key performance indicator of interest.

Abstract: An interventional tool stepper (30) employing a frame (31), a carriage (33), an optional gear assembly (32), and an optional grid template(34). The frame (31) is structurally configured to be positioned relative to an anatomical region for holding an interventional tool (40) relative to the anatomical region. The carriage (33) is structurally configured to hold the interventional tool (40) relative to the anatomical region. The gear assembly (32) is structurally configured to translate and/or rotate the carriage (33) relative to the frame (31). The grid template (34) is structurally configured to guide one or more additional interventional tools (41) relative to the anatomical region. The frame (31), the carriage (33), the optional gear assembly (32) and the optional grid template (34) have an electromagnetic-compatible material composition for minimizing any distortion by the interventional tool stepper (30) of an electromagnetic field.

Abstract: A training system and method includes a subject phantom (102) capable of being visualized on a display (120). A spatial tracking system (104) is configured to track an interventional instrument (108) in subject phantom space. A simulation system (110) is configured to generate a simulated abnormality in the phantom space and to simulate interactions with the simulated abnormality to provide feedback and evaluation information to a user for training the user in an associated procedure related to the abnormality.

Abstract: A controller for preparing an image for segmenting includes a memory that stores instructions, and a processor that executes the instructions. When executed by the processor, the instructions cause the controller to perform a process that includes displaying a first modeled tissue structure of a first type, and displaying an image of a first tissue structure of the first type separate from the first modeled tissue structure. The process also includes identifying, on the first modeled tissue structure, landmarks on the first modeled tissue structure for identification on the image of the first tissue structure, and sequentially accentuating each landmark on the first modeled tissue structure. The processor identifies locations on the image of the first tissue structure for each landmark on the first modeled tissue structure. The landmarks on the first modeled tissue structure are mapped to the locations identified on the image of the first tissue structure.

Abstract: System (SYS) and delated methods for supporting an imaging operation of an imaging apparatus (IA) capable of assuming different imaging geometries. The system comprises an input interface (IN) for receiving a current image acquired by the imaging apparatus (IA) of a current region of interest (ROI_1) at a current imaging geometry (p). A pre-trained machine learning component (MLC) computes output data that represents an imaging geometry change (?p) for a next imaging geometry (p?) in relation to a next region of interest (ROI_2). An output interface (OUT) outputs a specification of the imaging geometry change.

Abstract: An interventional therapy system may include at least one catheter configured for insertion within an object of interest (OOI); and at least one controller which configured to: obtain a reference image dataset including a plurality of image slices which form a three-dimensional image of the OOI; define restricted areas (RAs) within the reference image dataset; determine location constraints for the at least one catheter in accordance with at least one of planned catheter intersection points, a peripheral boundary of the OOI and the RAs defined in the reference dataset; determine at least one of a position and an orientation of the distal end of the at least one catheter; and/or determine a planned trajectory for the at least one catheter in accordance with the determined at least one position and orientation for the at least one catheter and the location constraints.

Abstract: The present disclosure describes ultrasound systems and methods configured to determine the elasticity of a target tissue. Systems can include an ultrasound transducer configured to acquire echoes responsive to ultrasound pulses transmitted toward the tissue, which may include a region of increased stiffness. Systems can also include a beamformer configured to control the transducer to transmit a push pulse into the tissue, thereby generating a shear wave in the region of increased stiffness. The beamformer can be configured to control the transducer to emit tracking pulses adjacent to the push pulse. Systems can further include a processor configured to determine a displacement amplitude of the shear wave and based on the amplitude, generate a qualitative tissue elasticity map of the tissue. The processor can combine the qualitative map with a quantitative map of the same tissue, and based on the combination, determine a boundary of the region of increased stiffness.

Abstract: Ultrasound image devices, systems, and methods are provided. An ultrasound imaging system comprising a processor circuit in communication with an ultrasound probe comprising a transducer array, wherein the processor circuit is configured to receive, from the ultrasound probe, a first image of a patients anatomy; detect, from the first image, a first anatomical landmark at a first location along a scanning trajectory of the patients anatomy; determine, based on the first anatomical landmark, a steering configuration for steering the ultrasound probe towards a second anatomical landmark at a second location along the scanning trajectory; and output, to a display in communication with the processor circuit, an instruction based on the steering configuration to steer the ultrasound probe towards the second anatomical landmark at the second location.

Abstract: Image co-registration entails: emitting energy, and responsively and dynamically acquiring images, the acquired images having a given dimensionality; selecting, repeatedly, and dynamically with the acquiring, from among the acquired images and, as a result of the selecting, changing, repeatedly, and dynamically, membership in a set of images of the given dimensionality; and, synchronously with the change, dynamically and iteratively registering the set to an image having a dimensionality higher than the given dimensionality. The co-registration is realizable with an imaging probe for the acquiring, and a tracking system for tracking a location, and orientation, of the probe, the registering being specialized for the acquiring with the probe being dynamically, during the acquiring, any one or more of angulated, rotated and translated.

Abstract: An ultrasound imaging device (10) with an ultrasound probe (12) acquires a live ultrasound image which is displayed with a contour (62) or reference image (60) registered with the live ultrasound image using a composite transform (42). To update the composite transform, the ultrasound imaging device acquires a baseline three-dimensional ultrasound (3D-US) image (66) tagged with a corresponding baseline orientation of the ultrasound probe measured by a probe tracker, and one or more reference 3D-US images (70) each tagged with a corresponding reference orientation. Transforms (54) are computed to spatially register each reference 3D-US image with the baseline 3D-US image. A closest reference 3D-US image is determined whose corresponding orientation is closest to a current orientation of the ultrasound probe as measured by the probe tracker. The composite transform is updated to include the transform to spatially register the closest reference 3D-US image to the baseline 3D-US image.

Abstract: A system for dynamic localization of medical instruments includes an ultrasound imaging system (110) configured to image a volume where one or more medical instruments are deployed. A registration module (136) registers two images of the one or more medical instruments to compute a transform between the two images, the two images being separated in time. A planning module (142) is configured to have positions of the volume and the one or more medical instruments updated based on the transform and, in turn, update a treatment plan in accordance with the updated positions such that changes in the volume and positions of the one or more medical instruments are accounted for in the updated plan.

Abstract: A system and method for planning and performing an interventional procedure based on the spatial relationships between identified points. The system includes a storage device (102) having an image (104) which includes a plurality of targets (107). A spatial determination device (114) is configured to determine distances and/or orientation between each of the targets. The system is configured to compare the distances and generate a warning signal if at least one of the distances is less than a minimum threshold (128). An image generation device (116) is configured to generate a graphical representation for display to the user which shows the spatial information between a selected target with respect to the other targets. A planning device (126) is configured to modify or consolidate targets automatically or based on a user's input in order to more effectively plan or execute an interventional procedure.

Abstract: A system (200) and method (900): access (910) a 3D reference image of a region of interest (ROI) (10) in a subject which was obtained using a first 3D imaging modality; segment (920) the ROI in the 3D reference image to define (930) a reference 3D coordinate system; acquire (940) 2D acoustic images of the ROI without absolute spatial tracking; generate (950) a standardized predicted pose for the 2D acoustic images with respect to a standardized 3D coordinate system (400) which was defined for a plurality of previously-obtained 3D images of corresponding ROIs in a plurality of other subjects which were obtained using the first 3D imaging modality; convert (960) the standardized predicted poses for the 2D acoustic images from the standardized 3D coordinate system to reference predicted poses in the reference 3D coordinate system; and use (970) the reference predicted poses for the 2D acoustic images to register the 2D acoustic images to the 3D reference image.

Abstract: Image co-registration (S390) entails: emitting energy, and responsively and dynamically acquiring images (216), the acquired images having a given dimensionality; selecting, repeatedly, and dynamically with the acquiring, from among the acquired images and, as a result of the selecting, changing, repeatedly, and dynamically, membership in a set (226) of images of the given dimensionality; and, synchronously with the change (S376), dynamically and iteratively registering the set to an image having a dimensionality higher than the given dimensionality. The co-registration is realizable with an imaging probe (140) for the acquiring, and a tracking system for tracking a location, and orientation, of the probe, the registering being specialized for the acquiring with the probe being dynamically, during the acquiring, any one or more of angulated, rotated and translated.

Abstract: A controller for qualifying image registration includes a memory that stores instructions; and a processor that executes the instructions. When executed by the processor, the instructions cause the controller to execute a process that includes receiving first imagery of a first modality and receiving second imagery of a second modality. The process executed by the controller also includes registering the first imagery of the first modality to the second imagery of the second modality to obtain an image registration. The image registration is subjected to an automated analysis as a qualifying process to qualify the image registration. The image registration is variably qualified when the image registration passes the qualifying process, and is not qualified when the image registration does not pass the qualifying process.

Abstract: A system (200) and method (1000): employ an acoustic probe (220) to acquire a series of two dimensional (2D) acoustic images of a region of interest (ROI) (290) in a subject without spatial tracking of the acoustic probe; predict a pose for each of the 2D acoustic images of the ROI in the subject with respect to a standardized three dimensional (3D) coordinate system (500) by applying the 2D acoustic images to a convolutional neural network (600) which has been trained using a plurality of previously-obtained 2D acoustic images of corresponding ROIs in a plurality of other subjects which were obtained with spatial tracking; and use the predicted pose for each of the 2D acoustic images of the ROI in the subject with respect to the standardized 3D coordinate system to produce a 3D acoustic image (820) of the ROI from the series of 2D acoustic images of the ROI.

Abstract: A training data modification system (TDM) for machine learning and related methods. The system comprises a data modifier (DM) configured to perform a modification operation to modify medical training X-ray imagery of a patient. The modification operation causes image structures in the modified medical training imagery. The image structure is representative of a property of i) a medical procedure, ii) an image acquisition operation by an X-ray-based medical imaging apparatus (IA), iii) an anatomy of the patient.

Abstract: A system for boundary identification includes a memory (42) to store shear wave displacements through a medium as a displacement field including a spatial component and a temporal component. A directional filter (206, 208) filters the displacement field to provide a directional displacement field. A signal processing device (26) is coupled to the memory to execute a boundary estimator (214) to estimate a tissue boundary in a displayed image based upon a history of the directional displacement field accumulated over time.

Abstract: A system includes an acoustic probe and an acoustic imaging machine. The acoustic probe includes a substrate with first and second principal surfaces, a device insertion port with an opening passing through the substrate from the first principal surface to the second principal surface, and an array of acoustic transducer elements supported by the substrate and disposed around the device insertion port. The acoustic imaging machine may systematically vary the size and/or position of the active acoustic aperture of the probe by providing transmit signals to selected acoustic transducer elements to cause the array to transmit an acoustic probe signal to an area of interest and may record a feedback signal of the transmit signals from an acoustic receiver provided at a distal end of an interventional device passed through the device insertion port into the area of interest to find an active acoustic aperture having optimal acoustic performance.

Abstract: An acoustic probe connectable to an imaging system. The acoustic probe has a substrate with first and second principal surfaces, at least one device insertion port comprising an opening passing through the substrate from the first principal surface to the second principal surface, and an array of acoustic transducer elements supported by the substrate and disposed around the at least one device insertion port. The acoustic probe comprising an instrument guide disposed within the device insertion port, the instrument guide being configured to selectively allow the interventional device to move freely within the device insertion port and to selectively lock the interventional device within the device insertion port in response to a user input via a user interface connected to the acoustic probe.