We propose a method to transfer a given pathology image stained by some immunostaining to a H&E stained one. When one construct a classifier that estimates the subtype of malignant lymphoma from a given H&E stained pathology image, one needs a set of training H&E stained whole slide images in which the tumor regions are annotated. The annotation is not easy and requires large human resources. Here, it is known that some immunostaining stains only some specific tumor cells and the tumor region detection from the immunostained images is straightforward. It means once you transfer the immunostained images to H&E stained ones, you can easily obtain a set of virtually H&E stained images with annotation of tumor regions. In this manuscript, we report on the proposed method and experimental results of stain transfer from CD20 stained images to H&E stained ones.
We proposed a method that detects DLBCL (Diffuse Large B-Cell Lymphoma) regions from a H&E stained whole slide pathology image by measuring the size of each nucleus. It is known that DLBCL cells would have about 2 to 3 times larger nuclei than typical lymphocytes. One can hence detect DLBCL regions by detecting every cell nucleus in a given H&E stained pathology image and describing the spatial distribution of the large nuclei. For the detection of cell nuclei, we employ a U-Net and a Bayesian U-Net. We describe the details of the proposed method and report the experimental results, which demonstrate the proposed method works well in the DLBCL regions.
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