Siemens Medical Solutions USA, Inc.

Siemens Aktiengesellschaft

The Cleveland Clinic Foundation

Singapore General Hospital

Randolph M Setser

Ning Xu

Richard D White

Thomas J O'Donnell

Engin DiKici

Jae Koul Kim

Engin Dikici

Kevin K'o Wen Chen

Arthur E Stillman

Ralf B Loeffler

A method for segmenting tubular structures in digital medical images includes extracting a subregion from a 3-dimensional (3D) digital medical image volume containing a vessel of interest, identifying potential vessel centerpoints for each voxel in the subregion by attaching to each voxel a tip of a 3D cone that is oriented in the direction of the voxel's image gradient and having each voxel within the cone vote for those voxels most likely to belong to a vessel centerline, selecting candidates for a second vote image that are both popular according to a first vote image, as well as being consistently voted upon by a radius image, reconfiguring the subregion as a graph where each voxel is represented by a node that is connected to 26 nearest neighbors by n-link edges, and applying a min-cut algorithm to segment the vessel within the subregion.

System and method for 3D vessel segmentation with minimal cuts

A system and method for imaging and identifying non-viable myocardial tissue in a patient's myocardium is disclosed. Images of a section of the myocardium are obtained. An endocardial border and epicardial border of the section of the myocardium is segmented. The section of the myocardium is divided into sectors. One or more selected features of the sectors of the myocardial wall are measured and applied to a decision surface. A determination is made as to whether each sector contains viable or non-viable myocardial tissue. An image that shows each sector of the myocardial wall and an indication of its viability is displayed.

System and method for using delayed enhancement magnetic resonance imaging and artificial intelligence to identify non-viable myocardial tissue

A method of magnetic resonance imaging of anatomy that is subject to a movement cycle (e.g., the heart during a cardiac cycle), comprising: administering a magnetic resonance contrast agent; waiting a period of time until the contrast agent is effective to cause selected portions of the anatomy (e.g., macrotic cardiac tissue) to have a different Trecovery rate from that of other portions (normal cardiac tissue); administering a plurality of inversion recovery pulses spaced in time; acquiring image data at a data acquisition time that is spaced in time by a known time interval following an inversion recovery pulse; varying the time within the movement cycle at which the inversion recovery pulses are administered so that the associated data acquisition times are at a plurality of phases of the movement cycle; processing image data acquired at a phase of the movement cycle to produce at least a portion of an image frame at that phase; and performing the processing for a plurality of phases of the movement cycle to produce a plurality of image frames corresponding to a plurality of phases

Acquiring contrast-enhanced, T1 weighted, cine magnetic resonance images

A system and method for tracking and classifying the left ventricle of the heart using cine-delayed enhancement magnetic resonance (Cine-DEMR) are provided. The method for tracking the left ventricle comprises: delineating myocardial borders of the left ventricle in an image of a first phase of a cardiac cycle of the heart; registering the image of the first phase with an image of a second phase of the cardiac cycle; copying the myocardial borders from the first phase onto the second phase; fitting the myocardial borders of the first phase to myocardial borders of the second phase; and refining the myocardial borders of the second phase.

System and method for tracking and classifying the left ventricle of the heart using cine-delayed enhancement magnetic resonance

A method and device for image processing to determine image characteristics includes operations of segmenting of first images to create segmentation contours corresponding to the first images; and registering the segmented first images to second images. Further, operations of transferring the segmentation contours from the first images to second images; and fitting the transferred segmentation contours in the second images are performed.

Growing community of inventors

Shaker Heights, OH, United States of America

Randolph M Setser