Siemens Medical Solutions Usa, Inc.

Siemens Aktiengesellschaft

Siemens Healthcare Gmbh

Siemens Corporate Research, Inc.

Siemens Healthineers Ag

Huseyin Tek

Dorin Comaniciu

Mehmet Akif Gulsun

Bogdan Georgescu

Fernando Vega-Higuera

James P Williams

Puneet Sharma

Ali Kamen

Lucian Mihai Itu

Michael Scheuering

Dominik Bernhardt

Xudong Zheng

Alper Ayvaci

Tommaso Mansi

Yefeng Zheng

Frank Sauer

Tiziano Passerini

Gareth Funka-Lea

Ingmar Voigt

Helene C Houle

Shmuel Aharon

Ingo Schmuecking

Jianhua Shen

Ferit Akova

A system includes propagation logic configured to obtain one or more contours for one or more directed viewframes within viewframe data. The one or more contours each having a set of tracking points. The viewframe data further includes intermediate viewframes among the one or more directed viewframes. The propagation logic is configured propagate the one or more contours across the intermediate viewframes via iterative viewframe-to-viewframe propagation. The iterative viewframe-to-viewframe propagation include optical flow analysis to determine candidate locations for tracking points followed by one or more validations using motion priors and/or resolved feature tracking.

Contour motion propagation across viewframe data

For cardiac flow detection in echocardiography, by detecting one or more valves, sampling planes or flow regions spaced from the valve and/or based on multiple valves are identified. A confidence of the detection may be used to indicate confidence of calculated quantities and/or to place the sampling planes.

Cardiac flow detection based on morphological modeling in medical diagnostic ultrasound imaging

A method and system for non-invasive assessment of coronary artery stenosis is disclosed. Patient-specific anatomical measurements of the coronary arteries are extracted from medical image data of a patient acquired during rest state. Patient-specific rest state boundary conditions of a model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Patient-specific rest state boundary conditions of the model of coronary circulation representing the coronary arteries are calculated based on the patient-specific anatomical measurements and non-invasive clinical measurements of the patient at rest. Hyperemic blood flow and pressure across at least one stenosis region of the coronary arteries are simulated using the model of coronary circulation and the patient-specific hyperemic boundary conditions. Fractional flow reserve (FFR) is calculated for the at least one stenosis region based on the simulated hyperemic blood flow and pressure.

Non-invasive functional assessment of coronary artery stenosis including simulation of hyperemia by changing resting microvascular resistance

A method and system for extracting coronary artery centerlines from 3D medical image volumes is disclosed. Heart chambers are segmented in a 3D volume. Coronary artery centerlines are initialized in the 3D volume coronary artery based on the segmented heart chambers. The coronary artery centerlines are locally refined based on a vesselness measure. A length of each coronary artery centerline is shrunk to verify that the coronary artery centerline is within a coronary artery. The coronary artery centerline is the extended using data-driven vessel tracing.

Method and system for coronary artery centerline extraction

Methods and systems for modeling cerebral aneurysm and their incoming and outgoing vessels from 3D image data are disclosed. Aneurysms and vessels are segmented from their background using a graph-cuts method. Begin and end of vessels are determined. Construction of a centerline of the incoming and outgoing vessels using a measure of vesselness in calculating a minimum cost path in a graph with nodes being representation of pixels is also disclosed. Vessel surface models are constructed from sub-voxel cross-sectional segmentation. The interpolation of vessels inside an aneurysm based on smooth continuity is disclosed. Selection of endo-vascular stents based on interpolation results is also provided.

Modeling cerebral aneurysms in medical images

A method for extracting a centerline of a tubular structure in a digital medical image includes providing a 3-dimensional (3D) digitized medical image having a segmented tubular structure, finding a path in the image between a starting point and every other point in the tubular structure that minimizes an accumulative cost function, wherein the minimum accumulative cost &#x3c6;(x) at a point x is a minimum of (&#x3c6;(x')+P) over all nearest neighbors x&#x2032; wherein Pis a cost of propagation obtained from the inverse of a medialness measure computed in a plane orthogonal to a line between x and x&#x2032; that is centered at a mid-point of the line, the medialness measure m(x) computed in a circular region C(x, R) centered at point x on the line, with radius R, given by &#x2003;wherein {right arrow over (u)}(&#x3b1;)=sin(&#x3b1;){right arrow over (u)}+cos(&#x3b1;){right arrow over (u)}and {right arrow over (u)}and {right arrow over (u)}define a 2D plane, and &#x192;(x,R{right arrow over (u)}(&#x3b1;)) is &#x2003;wherein M is the number of background points.

System and method for geometric modeling of tubular structures

A method of coronary vessel segmentation and visualization includes providing a digitized coronary image, placing a plurality of seed points along an estimated centerline of a coronary vessel, selecting a seed point and constructing a cyclic graph around the seed point in a plane perpendicular to the centerline at the seed point, performing a multi-scale-mean shift filtering in the perpendicular plane to estimate image gradient values, detecting a vessel boundary using a minimum-mean-cycle optimization that minimizes a ratio of a cost of a cycle to a length of a cycle, constructing a sub-voxel accurate vessel boundary about a point on the centerline, and refining the location of the centerline point from the sub-voxel accurate boundary, where the steps of constructing a sub-voxel accurate vessel boundary and refining the centerline point location are repeated until convergence.

System and method for coronary segmentation and visualization

A method for extracting a local center-axis representation of a vessel, includes: placing first and second seed points in an image that includes the vessel, wherein the first and second seed points are placed near a beginning and an end of a centerline of the vessel; representing the image as a discrete graph having nodes and edges, wherein the first seed point is a source node and the second seed point is a goal node; and finding a minimum-cost path between the first and second seed points by computing a cost of edges between the first and second seed points, wherein the cost of each edge is reciprocal to a vesselness measure of the edge.

Robust vessel tree modeling

A method for producing three-dimensional images of a blood vessel. A first set of seed points is placed along a first estimate of a centerline of the vessel. A cyclic graph is constructed around a first one of the seed points in a plane passing through the seed points. The graph comprises a plurality of nodes, with edges connecting the nodes. The nodes are disposed at equally spaced intervals about each one of a circumference of plurality of concentric circles centered at the seed point The method applies filtering such as multi-scale mean shift intensity detection orthogonal to the edges of the cyclic graph to thereby estimate a boundary of the vessel. A new center of the estimated boundary is determined to thereby generate a new seed point. The process is repeated using the new seed point to thereby generate a final boundary of the vessel in the plane.

Three-dimensional (3D) modeling of coronary arteries

Disclosed is a method and system for detecting a boundary of a vessel in an image. Edges in the image are detected. Edge detection is based on the change in intensity over some distance while varying the scale of the distance. A set of edges is then selected from the detected edges. An initial vessel boundary is determined based on the selected set, and a shape descriptor (e.g., one or more elliptical shape descriptors) is applied to the initial vessel boundary to determine a final vessel boundary.

Method and apparatus for detecting blood vessel boundaries using multi-scale mean-shift ray propagation

A system and method for artery-vein separation and vessel modeling are provided, the system including an adapter unit, a centerline locating unit in signal communication with the adapter unit, and a deformable modeling unit in signal communication with the centerline locating unit; and the method including receiving three-dimensional image data indicative of vessels, visualizing the received image data, selecting seed points on the vessels relative to the visualization, smoothing the image data with a non-linear filter responsive to curvature information of the data, initiating a deformable model for each selected seed point, modulating the propagation of each deformable model in accordance with at least one of local and global statistics, and growing an interconnected region for each model, where each model competes for classifying new points in its own region until convergence.

Artery-vein separation and vessel modeling

An exemplary method of segmenting an object from a structure of interest is provided. A user-selected point in an image is received. A watershed transformation is performed on the user-selected point to determine a primary object. A neighboring watershed region is added to the primary object based on region competition and a smoothness constraint to form an updated object.

Region competition via local watershed operators

We propose local watershed operators for the segmentation of structures, such as medical structures, from an image. A watershed transform is a technique for partitioning an image into many regions while substantially retaining edge information. The proposed watershed operators are a computationally efficient local implementation of watersheds, which can be used as an operator in other segmentation techniques, such as seeded region growing, region competition and markers-based watershed segmentation.

Local watershed operators for image segmentation

A method for segmentation of 3D structures in CT and MR images is provided. The method is based on 3D ray propagation by mean-shift analysis with a smoothness constraint. Ray propagation is used to guide an evolving surface due to its computational efficiency and shape priors are incorporated for robust convergence. The method includes the steps of receiving 3D image data; visualizing the 3D image data on a display device; selecting a structure in the 3D image data by placing a seed in the structure; initializing a plurality of rays from the seed to form a surface; determining a speed function of each of the rays; evolving the surface by propagating the rays based on the speed function of each of the rays; converging the rays on a boundary of the structure; and segmenting the structure when all of the rays have converged on the structure's boundary.

Growing community of inventors

Princeton, NJ, United States of America

Huseyin Tek