Automatic Visualization of Regional Functional Parameters of Left Ventricle from Cardiac Imaging

US2016110879A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2016110879-A1
Application numberUS-201414536616-A
CountryUS
Kind codeA1
Filing dateNov 8, 2014
Priority dateOct 18, 2014
Publication dateApr 21, 2016
Grant date

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Abstract

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A method for automatically identifying and localizing anatomical regions of a left ventricle of a heart using a segment model, the method including receiving a volumetric MR image series of one or more time-points in a heart cycle with associated myocardial boundaries, representing the heart, performing a long-axis partitioning on each image of the volumetric image series, performing a short-axis partitioning volumetric image series, generating a polar map, wherein each image of the volumetric image series is mapped to a location on the polar map, wherein the location is characterized using the long-axis partitioning and the short-axis partitioning, and generating a mapping from the polar map to a voxel in an associated image of the volumetric image series representing an anatomical location.

First claim

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1 - 6 . (canceled) 7 . A computer program product for automatically identifying and localizing anatomical regions of a left ventricle of a heart using a segment model, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: receiving a volumetric image series of one or more time-points in a heart cycle with associated myocardial boundaries, representing the heart; performing a long-axis partitioning on each image of the volumetric image series; performing a short-axis partitioning volumetric image series; generating a polar map, wherein each image of the volumetric image series is mapped to a location on the polar map, wherein the location is characterized using the long-axis partitioning and the short-axis partitioning; and generating a mapping from the polar map to a voxel in an associated image of the volumetric image series representing an anatomical location. 8 . The computer program product of claim 7 , further comprising automatically generating the polar map. 9 . The computer program product of claim 7 , wherein a functional measurement is represented in the polar map by a color range and the anatomical location is directly related to a specific segment of the polar map. 10 . The computer program product of claim 7 , wherein the polar map displays regional functional parameters. 11 . The computer program product of claim 7 , the polar map has a 1-to-1 linkage to a corresponding image of the volumetric image series. 12 . The computer program product of claim 11 , further comprising receiving an indication of a location on the polar map and outputting a corresponding tissue or its functional parameters. 13 - 18 . (canceled)

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Classifications

  • Image post-processing, e.g. metal artefact correction · CPC title

  • Positron emission tomography [PET] · CPC title

  • Computed x-ray tomography [CT] · CPC title

  • Biomedical image inspection · CPC title

  • involving thresholding · CPC title

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What does patent US2016110879A1 cover?
A method for automatically identifying and localizing anatomical regions of a left ventricle of a heart using a segment model, the method including receiving a volumetric MR image series of one or more time-points in a heart cycle with associated myocardial boundaries, representing the heart, performing a long-axis partitioning on each image of the volumetric image series, performing a short-ax…
Who is the assignee on this patent?
IBM
What technology area does this patent fall under?
Primary CPC classification G06T7/20. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu Apr 21 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).