Quantitative imaging for cancer subtype

    公开(公告)号:US11120312B2

    公开(公告)日:2021-09-14

    申请号:US16203445

    申请日:2018-11-28

    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.

    Methods and systems for representing, storing, and accessing computable medical imaging-derived quantities

    公开(公告)号:US10755810B2

    公开(公告)日:2020-08-25

    申请号:US15237249

    申请日:2016-08-15

    Abstract: Methods and systems are disclosed for structuring and using information pertinent to in vivo biomarkers, specifically quantitative imaging biomarkers, using semantic web technology for personalized medicine and discovery science. It supports the development and application of statistical evidence at a level of granularity and sophistication more closely tied to the complexity of the disease itself and its underlying biology, including technology linking multiple biological scales, than has previously been eedisclosed. It provides data and computational services to analyze quantitative imaging and non-imaging data, coupled with multi-scale modeling to elucidate pre-symptomatic and clinical disease processes. It may be used to assess technical or analytical performance for its own sake and/or to further annotate the quantitative analysis. It supports statistical hypothesis testing to determine and present analytical performance, determine the clinical relevance and establish to what extent a biomarker is causally rather than coincidentally related in clinical contexts of use.

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