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Overcoming the limitations of patch-based learning to detect cancer in whole slide images.

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Mózes Gálffy

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The transition module: a method for preventing overfitting in convolutional neural networks., , , , и . Comput. methods Biomech. Biomed. Eng. Imaging Vis., 7 (3): 260-265 (2019)Determining tumor cellularity in digital slides using ResNet., , , , и . Medical Imaging: Digital Pathology, том 10581 из SPIE Proceedings, стр. 105810U. SPIE, (2018)Overcoming the limitations of patch-based learning to detect cancer in whole slide images., , , , , и . CoRR, (2020)Automated Segmentation of DCIS in Whole Slide Images., , , , и . ECDP, том 11435 из Lecture Notes in Computer Science, стр. 67-74. Springer, (2019)Transitioning Between Convolutional and Fully Connected Layers in Neural Networks., , , , и . DLMIA/ML-CDS@MICCAI, том 10553 из Lecture Notes in Computer Science, стр. 143-150. Springer, (2017)Localization and classification of cell nuclei in post-neoadjuvant breast cancer surgical specimen using fully convolutional networks., , , , , , и . Medical Imaging: Digital Pathology, том 10581 из SPIE Proceedings, стр. 105810O. SPIE, (2018)