COMBINED ASSESSMENT OF MORPHOLOGICAL AND PERIVASCULAR DISEASE MARKERS

    公开(公告)号:US20220392070A1

    公开(公告)日:2022-12-08

    申请号:US17890822

    申请日:2022-08-18

    Abstract: A system including a hierarchical analytics framework that can utilize a first set of machine learned algorithms to identify and quantify a set of biological properties utilizing medical imaging data is provided. System can segment the medical imaging data based on the quantified biological properties to delineate existence of perivascular adipose tissue. The system can also segment the medical imaging data based on the quantified biological properties to determine a lumen boundary and/or determine a cap thickness based on a minimum distance between the lumen boundary and LRNC regions.

    QUANTITATIVE IMAGING FOR DETECTING HISTOPATHOLOGICALLY DEFINED PLAQUE FISSURE NON-INVASIVELY

    公开(公告)号:US20220012877A1

    公开(公告)日:2022-01-13

    申请号:US17314766

    申请日:2021-05-07

    Abstract: Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

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