Method for Finding Image Regions that Significantly Influence Classification in a Tool for Pathology Classification in a Medical Image
AssigneesAgfa Healthcare NV, VRVIS Zentrum für Virtual Reality und Visualisierung Forschungs-GmbH
InventorsDavid Major, Dimitrios Lenis, Maria Wimmer, Gert Sluiter, Astrid Berg, Katja Buehler
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Abstract
A method for finding image regions that significantly influence classification in a tool for pathology classification in a medical image wherein image regions that influence classification are inpainted, by replacing the pixels in these regions by representations of heathy tissue, resulting in an image with a healthy classification-score in the classification tool.
Claims2
(canceled)
A method for inpainting image regions that influence classification in a classification tool for pathology classification in a medical image by replacing pixels in potentially pathological regions by pixels of heathy tissue, these regions being determined and inpainted by the following steps:
- randomly initializing a binary map, whose image regions are image regions of said medical image,
- overlapping said binary map to said medical image to generate an input image and inputting said input image in a partial convolution network,
- inputting the result of said partial convolution network to said classification tool, yielding a new classification score,
- optimizing the above initialized binary map using a loss function fed with (i) said map, (ii) said original image with a corresponding classification score, and (iii) said new classification score, and
- updating said binary map in successive steps by eliminating and creating new mask positions for the partial convolution network.
Dependencies are inferred from the claim text.