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Akihiko Yoshizawa

3 accepted papers

2020

Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology

ECCV 2020poster

In pathological diagnosis, since the proportion of the adenocarcinoma subtypes is related to the recurrence rate and the survival time after surgery, the proportion of cancer subtypes for pathological images has been recorded as diagnostic information in some hospitals. In this paper, we propose a s…

Cited by 27SourcePDFScholar
2019

Adaptive Weighting Multi-Field-Of-View CNN for Semantic Segmentation in Pathology

CVPR 2019poster

Automated digital histopathology image segmentation is an important task to help pathologists diagnose tumors and cancer subtypes. For pathological diagnosis of cancer subtypes, pathologists usually change the magnification of whole-slide images (WSI) viewers. A key assumption is that the importance…

Cited by 165PDFcodeScholar
2019

Multi-Stage Pathological Image Classification Using Semantic Segmentation

ICCV 2019accepted

Histopathological image analysis is an essential process for the discovery of diseases such as cancer. However, it is challenging to train CNN on whole slide images (WSIs) of gigapixel resolution considering the available memory capacity. Most of the previous works divide high resolution WSIs into s…

Cited by 54SourcePDFScholar