The importance of stain normalization in colorectal tissue classification with convolutional networks
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| Authors | Geert Litjens, Jeroen van der Laak, Iris Nagtegaal, Alexi Baidoshvili, Gabriel Silva de Souza, Oscar Geessink, Francesco Ciompi, Babak Ehteshami Bejnordi, Bram van Ginneken |
| Journal/Conference Name | Proceedings - International Symposium on Biomedical Imaging |
| Paper Category | Artificial Intelligence |
| Paper Abstract | The development of reliable imaging biomarkers for the analysis of colorectal cancer (CRC) in hematoxylin and eosin (H&E) stained histopathology images requires an accurate and reproducible classification of the main tissue components in the image. In this paper, we propose a system for CRC tissue classification based on convolutional networks (ConvNets). We investigate the importance of stain normalization in tissue classification of CRC tissue samples in H&E-stained images. Furthermore, we report the performance of ConvNets on a cohort of rectal cancer samples and on an independent publicly available dataset of colorectal H&E images. |
| Date of publication | 2017 |
| Code Programming Language | Python |
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