Sequential integration of adversarial networks with handcrafted features (SANwicH): identifying sites of prognostic significance for predicting cancer recurrence
AssigneeCase Western Reserve University
InventorsAnant Madabhushi, Xiangxue Wang
Life of this patent
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Abstract
Embodiments discussed herein facilitate generation of a prognosis for a medical condition based on determination of one or more histomorphometric features for tiles of a whole slide image (WSI) that have been identified as the most prognostically significant tiles of the WSI. A first set of embodiments discussed herein relates to training of a fully convolutional network (FCN) to determine the prognostic significance of pixels of a WSI. A second set of embodiments discussed herein relates to determination of a prognosis based on analysis of regions identified as the most prognostically significant by a trained FCN.
Claims18
A non-transitory computer-readable medium storing computer-executable instructions that, when executed, cause a processor to perform operations, comprising:
- accessing a digitized whole slide image (WSI) of tissue associated with a medical condition, wherein the digitized WSI comprises a plurality of pixels, wherein each pixel of the plurality of pixels has an associated intensity;
- analyzing the digitized WSI with an adversarially trained fully convolutional network (FCN) to determine, for each pixel of the plurality of pixels, an associated prognostic significance (PS) for that pixel;
- generating a PS map corresponding to the digitized WSI that indicates, for each pixel of the plurality of pixels, the associated PS for that pixel;
- dividing the digitized WSI into a plurality of tiles, wherein each tile of the plurality of tiles is a square comprising an associated k×k pixels of the plurality of pixels, wherein each tile has a tile PS based on the associated PS of each pixel of the associated k×k pixels of that tile;
- selecting N tiles of the plurality of tiles, wherein the selected N tiles have N highest tile PS among tiles of the plurality of tiles;
- computing, for each of the N tiles, an associated prognostic metric for that tile based on one or more histomorphometric features;
- and
- generating a prognosis for the digitized WSI in connection with the medical condition based on the associated prognostic metric computed for each tile of the N tiles.
An apparatus that facilitates generation of a prognosis in connection with a medical condition, the apparatus comprising:
- a processor;
- a memory configured to store a digitized whole slide image (WSI) of tissue associated with the medical condition, wherein the digitized WSI comprises a plurality of pixels, wherein each pixel of the plurality of pixels has an associated intensity;
- an input/output (I/O) interface;
- a set of circuits;
- and
- an interface that connects the processor, the memory, the I/O interface, and the set of circuits, the set of circuits comprising:
- an image acquisition circuit configured to access the digitized WSI;
- an adversarial fully convolutional network circuit configured to:
- analyze the digitized WSI to determine, for each pixel of the plurality of pixels, an associated prognostic significance (PS) for that pixel;
- generate a PS map corresponding to the digitized WSI that indicates, for each pixel of the plurality of pixels, the associated PS for that pixel;
- divide the digitized WSI into a plurality of tiles, wherein each tile of the plurality of tiles is a square comprising an associated k×k pixels of the plurality of pixels, wherein each tile has a tile PS based on the associated PS of each pixel of the associated k×k pixels of that tile;
- and
- select N tiles of the plurality of tiles, wherein the selected N tiles have N highest tile PS among tiles of the plurality of tiles;
- a histomorphometric feature calculation circuit configured to:
- compute, for each of the N tiles, an associated prognostic metric for that tile based on one or more histomorphometric features;
- and
- generate the prognosis for the digitized WSI in connection with the medical condition based on the associated prognostic metric computed for each tile of the N tiles;
- and
- a display circuit configured to output the prognosis for the digitized WSI in connection with the medical condition.
Dependencies are inferred from the claim text.