Detection of left ventricular wall motion abnormalities from volume rendering of 4dct cardiac angiograms using deep learning

HIGHLIGHTS

  • who: Elliot McVeigh from the United Kingdom Amsterdam University Medical have published the research: Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning, in the Journal: (JOURNAL)
  • what: The authors propose a novel framework which combines volume rendering videos of clinical cardiac CT cases with a DL classification to detect WMA. The authors propose to directly view 3D regions of wall motion abnormalities through the use of volumetric visualization techniques such as volume rendering (VR) , which can preserve high resolution anatomical information and visualize 3D and 4D . . .

     

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