Monte-Carlo Sampling Applied to Multiple Instance Learning for Histological Image Classification

Author:

Combalia MarcORCID,Vilaplana VerónicaORCID

Publisher

Springer International Publishing

Reference11 articles.

1. BACH: Iciar 2018 (2018). https://iciar2018-challenge.grand-challenge.org/

2. Campanella, G., Werneck Krauss Silva, V., Fuchs, T.J.: Terabyte-scale deep multiple instance learning for classification and localization in pathology, May 2018

3. Carithers, L.J., et al.: A novel approach to high-quality postmortem tissue procurement: the GTEx project. Biopreservation Biobanking 13(5), 311–319 (2015)

4. He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR abs/1512.03385 (2015). http://arxiv.org/abs/1512.03385

5. Hou, L., Samaras, D., Kurc, T.M., Gao, Y., Davis, J.E., Saltz, J.H.: Patch-based convolutional neural network for whole slide tissue image classification. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2424–2433 (2016)

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