Negative Pseudo Labeling using Class Proportion for Semantic Segmentation in Pathology

ECCV 2020 Hiroki TokunagaBrian Kenji IwanaYuki TeramotoAkihiko YoshizawaRyoma Bise

We propose a weakly-supervised cell tracking method that can train a convolutional neural network (CNN) by using only the annotation of "cell detection" (i.e., the coordinates of cell positions) without association information, in which cell positions can be easily obtained by nuclear staining. First, we train a co-detection CNN that detects cells in successive frames by using weak-labels... (read more)

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