Detection of Gastric Cancer from Histopathological Image using Deep Learning with Weak LabelDownload PDF

11 Apr 2018 (modified: 16 May 2018)MIDL 2018 Abstract SubmissionReaders: Everyone
  • Abstract: We propose an automatic method to detect gastric cancer on whole slide images. To do this, we collected cases with slide-level and region-level labels and trained deep neural network for tissue classification. To improve the tissue classification performance, we exploited slide-level weak label for training the model with patches without region-level label. For whole slide classification, we extracted features representative for whole slide characteristics. The proposed method archived 92.51% accuracy on 3 class classification. Macro-average and microaverage AUROC on the test set is 0.9802 and 0.9788.
  • Keywords: Digital pathology, Gastric cancer, Deep learning, Medical imaging, Weak Label
  • Author Affiliation: Vuno Inc., Green Cross Laboratories
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