US 2026/0065699 A1Published application

Tissue pathology reading support device and method therefor

AssigneeSeegene Medical Foundation

InventorsJong Kee CHUN, Young Sin KO, Ji Wouk CHANG

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Abstract

The present specification provides a tissue pathology reading support device and a method therefor, which, with respect to an artificial intelligence model, divide, into a plurality of patches, a slide tissue image for learning that indicates a lesion site if a lesion is present, infer the classification of each of the plurality of patches so as to learn patch classification results, integrate the plurality of patches and the patch classification results so as to infer the classification of the reconstructed slide tissue image, thereby learning slide tissue image classification results, use the trained artificial intelligence model so as to infer the classification of each of the plurality of patches, thereby generating patch classification results, and integrate the plurality of patches and the patch classification results so as to infer the classification of the reconstructed slide tissue image, thereby generating slide tissue image classification results.

Claims20

Dependent claims

A histopathologic reading support device, comprising:

an input unit inputting slide information and a slide tissue image;
a pre-processing unit dividing the input slide tissue image into a plurality of patches;
a tissue classification unit generating a patch classification result by inferring a classification of each of the plurality of patches using a trained artificial intelligence model, and generating a slide tissue classification result by inferring a classification of a slide tissue image reconstructed by integrating the plurality of patches and the classification results of the patches;
a storage unit storing the slide information and the slide tissue image, the plurality of patches, patch information about the patches, the patch classification result, and the slide tissue image classification result;
and
an output unit outputting the patch classification result of each of the plurality of patches and the slide tissue image classification result,
wherein when there is a lesion, the trained artificial intelligence model is trained with patch classification results by dividing a training slide tissue image marked with a site of the lesion into a plurality of patches using the pre-processing unit and inferring a classification of each of the plurality of patches and is trained with a slide tissue image classification result by inferring a classification of a slide tissue image reconstructed by integrating the plurality of patches and the classification results of the patches.

4 more elements

A histopathologic reading support method, comprising:

an input step inputting slide information and a slide tissue image;
a pre-processing step dividing the input slide tissue image into a plurality of patches;
when there is a lesion, a training step training an artificial intelligence model with patch classification results by dividing a training slide tissue image marked with a site of the lesion into a plurality of patches and inferring a classification of each of the plurality of patches and training the artificial intelligence model with a slide tissue image classification result by inferring a classification of a slide tissue image reconstructed by integrating the plurality of patches and the classification results of the patches;
a tissue classification step generating a patch classification result by inferring a classification of each of the plurality of patches using a trained artificial intelligence model, and generating a slide tissue image classification result by inferring a classification of a slide tissue image reconstructed by integrating the plurality of patches and the classification results of the patches;
a storage step storing the slide information and the slide tissue image, the plurality of patches, patch information about the patches, the patch classification result, and the slide tissue image classification result;
and
an output step outputting the patch classification result of each of the plurality of patches and the slide tissue image classification result.

4 more elements

Dependencies are inferred from the claim text.