A method and system for automatic location of a target treatment structure, such as a pulmonary vein ostium, from an anatomical image. The method includes calculating a most likely path of blood flow through a pulmonary vein based on a cross-sectional area minimization technique and calculating pulmonary vein geometry as a function of length. For example, a pulmonary vein ostium may be located by analyzing a change in pulmonary vein dimensional size or other anatomical factors, such as absolute size. The method may also include determining tissue thickness at the pulmonary vein ostium or other treatment size for treatment dose optimization. The method may be an algorithm performed by a processing unit of a navigation system or other component of a medical system.

A robotic system includes a robot having an associated workspace; a vision sensor constructed to obtain a 3D image of a robot scene including a workpiece located in the workspace; and a control system communicatively coupled to the vision sensor and to the robot. The control system is configured to execute program instructions to filter the image by segmenting the image into a first image portion containing substantially only a region of interest within the robot scene, and a second image portion containing the balance of the robot scene outside the region of interest; and by storing image data associated with the first image portion. The control system is operative to control movement of the robot to perform work, on the workpiece based on the image data associated with the first image portion.

Aspects of the present disclosure involve systems, methods, computer program products, manufacturing processes and the like, for utilizing a series of images of a patient's anatomy to determine an estimation of relevant lengths and angles and other dimensions for use during a hip replacement procedure, which may be used to create one or more femur and/or acetabulum cavity implants or inserts useful in a partial or total hip replacement. In one particular embodiment, a jig mechanism for providing a scraper of the acetabulum cavity may be created with the information of the patient's anatomy. Further, the location of these features in the images may be determined by analyzing the gray scale value of one or more pixels around a selected point on the image. The pixel with the lowest gray scale value may then be assumed to be the edge of the cortical bone in the 2D image.

In part, the invention relates to systems and methods of calibrating a plurality of frames generated with respect to a blood vessel as a result of a pullback of an intravascular imaging probe being pullback through the vessel. A calibration feature disposed in the frames that changes between a subset of the frames can be used to perform calibration. Calibration can be performed post-pullback. Various filters and image processing techniques can be used to identify one or more feature in the frames including, without limitation, a calibration feature, a guidewire, a side branch, a stent strut, a lumen of the blood vessel, and other features. The feature can be displayed using a graphic user interface.

In part, the invention relates to systems and methods of calibrating a plurality of frames generated with respect to a blood vessel as a result of a pullback of an intravascular imaging probe being pullback through the vessel. A calibration feature disposed in the frames that changes between a subset of the frames can be used to perform calibration. Calibration can be performed post-pullback. Various filters and image processing techniques can be used to identify one or more feature in the frames including, without limitation, a calibration feature, a guidewire, a side branch, a stent strut, a lumen of the blood vessel, and other features. The feature can be displayed using a graphic user interface.

The present invention relates to a device for segmenting an image of a subject (36), comprising a data interface for receiving an image of said subject (36), said image depicting a structure of said subject (36), a translation unit for translating a user-initiated motion of an image positioner means into a first contour (38) surrounding said structure, a motion parameter registering unit for registering a motion parameter of said user-initiated motion to said first contour (38), said motion parameter comprising a speed and/or an acceleration of said image positioner means, an image control point unit for distributing a plurality of image control points (40) on said first contour with a density decreasing with said motion parameter, and a segmentation unit for segmenting said image by determining a second contour (44) within said first contour based on said plurality of image control points (40), said segmentation unit being configured to use one or more segmentation functions.

A medical imaging system (5) includes a workstation (20), a coarse segmenter (30), a fine segmenter (32), and an enclosed tissue identification module (34). The workstation (20) includes at least one input device (22) for receiving a selected location as a seed in a first contrasted tissue type and a display device (26) which displays a diagnostic image delineating a first segmented region of a first tissue type and a second segmented region of a second contrasted tissue type and identified regions which include regions fully enclosed by the first segmented region as a third tissue type. The coarse segmenter (30) grows a coarse segmented region of coarse voxels for each contrasted tissue type from the seed location based on a first growing algorithm and a growing fraction for each contrasted tissue type. The seed location for growing the second contrasted tissue type includes the first coarse segmented region and any fully enclosed coarse voxels, and each coarse voxel includes an aggregation of voxels and a maximum and a minimum of the voxel intensities. The fine segmenter (32) grows a segmented region of voxels for each contrasted tissue type from the seed location and bounded by the second coarse segmented region based on a second growing algorithm and a growing fraction for each contrasted tissue type initially set to the growing fraction for the corresponding region. The seed location for growing the second contrasted tissue type includes the first segmented region and any identified regions. The enclosed tissue identification module (34) identifies any regions of voxels fully enclosed by the first segmented region as being of the third tissue type. The coarse segmenter, the fine segmenter, and the enclosed tissue identification module are implemented by an electronic data processing device.

According to one embodiment, a pattern outline extraction device includes a control unit, a secondary storage unit and a memory. The control unit reads the image data of the patterns formed by changing the process condition, and extracts outlines of the patterns from the image data. The control unit superposes the outlines, and sets straight measurement lines. The control unit calculates variations on the measurement lines relative to measurement points on the measurement lines at points of intersection of the measurement lines and the outlines, and calculates variation-process condition correspondence information. The control unit calculates predicted variations on the measurement lines relative to the measurement points corresponding to a desired process condition based on the variation-process condition correspondence information, calculates calculated points that are obtained by adding the predicted variations to the measurement points on the measurement lines, and calculates a predicted outline by connecting the calculated points.

A method for use in medical imaging of a patient including, with the patient immobilized with respect to an imaging reference frame, acquiring first digital imaging information including a first region of interest using a first imaging modality; processing the first digital imaging information to identify a feature for analysis; and using a second imaging modality to acquire targeted second imaging information for a second region of interest, the second region of interest corresponding to a subset of the first region of interest, wherein the second region of interest includes the feature for analysis. An apparatus for use in medical imaging comprising structure for immobilizing a patient with respect to an imaging reference frame; a first imaging system for acquiring first digital imaging information including a first region of interest using a first imaging modality; a processor processing the first digital imaging information using a diagnostic tool to identify a feature of interest; and a second imaging system for acquiring second imaging information using a second imaging modality, the second imaging information corresponding to a second region of interest including the feature for analysis.

Systems and methods are herein provided for annotation and segmentation of 3D multi-volume imaging data. In one example, a method comprises obtaining three-dimensional (3D) multi-volume imaging data, the 3D multi-volume imaging data comprising a plurality of registered image volumes; determining one or more positions of a user cursor within a first image of a first image volume of the plurality of registered image volumes; determining a contour point position corresponding to each of the one or more positions of the user cursor for two or more of the plurality of registered image volumes; generating two or more segmentation contours corresponding to the two or more of the plurality of registered image volumes; determining, via user input, a selected segmentation contour of the two or more segmentation contours; generating a 3D segmentation mask based at least in part on the selected segmentation contour and saving the 3D segmentation mask to memory.