| CPC G16H 30/20 (2018.01) [G06N 20/00 (2019.01); G06T 7/0012 (2013.01); G16H 50/20 (2018.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01)] | 19 Claims |
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1. A method for identifying cancerous tissue based on histopathological slides comprises:
a. obtaining first image information associated with a first histopathological slide of prostate tissue, wherein the histopathological slide is divided into a plurality of tiles and the first image information is associated with a first tile of the plurality of tiles and second image information is associated with a second tile of the plurality of tiles;
b. classifying the first image information using a first machine learning algorithm trained using a first training set, where the first image information is an input and the machine learning algorithm provides first classification information associated with the first image information associated with a risk of cancer;
c. generating mask information indicating risk of cancer based on the first classification information provided in the classifying step; and
d. providing the mask information to a user interface, wherein the user interface is configured to display the first image information and the mask information to highlight portions of the first image information associated with risk of cancer, wherein a user interacts with the mask information via the user interface to obtain additional information associated with risk of cancer and to provide feedback information associated with the mask information, wherein the feedback information is stored in the first training set and used to train the first machine learning algorithm;
e. obtaining the second image information;
f. classifying the second image information using the first machine learning algorithm trained using the first training set, where the second image information is an input and the first machine learning algorithm provides second classification information associated with the second image information associated with the risk of cancer;
g. generating updated mask information indicating risk of cancer based on the first classification information and the second classification information;
h. providing the updated mask information to the user interface, wherein the user interface is configured to display the first image information, the second image information and the updated mask information to highlight portions of the first image information and the second image information associated with risk of cancer,
i. repeating steps (e) to (h) for each tile of the plurality of tiles; and
j. classifying a whole slide image of the histopathological slide associated with the first image information and the second image information based on the first image information, the second image information and image information associated with each tile of the plurality of tiles, including clustering at least the first image information, the second image information and the image information associated with each tile of the plurality of tiles and encoding a whole slide image histogram based on the clustered information.
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