A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology

@inproceedings{Paeng2017AUF,
  title={A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology},
  author={Kyunghyun Paeng and Sangheum Hwang and Sunggyun Park and Minsoo Kim and Seokhwi Kim},
  booktitle={DLMIA/ML-CDS@MICCAI},
  year={2017}
}
We present a unified framework to predict tumor proliferation scores from breast histopathology whole slide images. Our system offers a fully automated solution to predicting both a molecular data-based, and a mitosis counting-based tumor proliferation score. The framework integrates three modules, each fine-tuned to maximize the overall performance: An image processing component for handling whole slide images, a deep learning based mitosis detection network, and a proliferation scores… CONTINUE READING
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Faster rcnn : Towards real - time object detection with region proposal networks

  • P. Van Diest, E. Van Der Wall, J. Baak
  • Advances in neural information processing systems
  • 2015

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