Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering

Xu, Yan; Zhu, Jun-Yan; Chang, Eric I-Chao; Tu, Zhuowen

doi:10.1109/CVPR.2012.6247772

Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering

Yan Xu, Jun-Yan Zhu, Eric I-Chao Chang, Zhuowen Tu

CVPR 2012 pp. 964-971

doi:10.1109/CVPR.2012.6247772 /cvpr/2012/xu2012cvpr-multiple/

Abstract

Cancer tissues in histopathology images exhibit abnormal patterns; it is of great clinical importance to label a histopathology image as having cancerous regions or not and perform the corresponding image segmentation. However, the detailed annotation of cancer cells is often an ambiguous and challenging task. In this paper, we propose a new learning method, multiple clustered instance learning (MCIL), to classify, segment and cluster cancer cells in colon histopathology images. The proposed MCIL method simultaneously performs image-level classification (cancer vs. non-cancer image), pixel-level segmentation (cancer vs. non-cancer tissue), and patch-level clustering (cancer subclasses). We embed the clustering concept into the multiple instance learning (MIL) setting and derive a principled solution to perform the above three tasks in an integrated framework. Experimental results demonstrate the efficiency and effectiveness of MCIL in analyzing colon cancers.

CVPR Semantic Scholar

Cite

Text

Xu et al. "Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012. doi:10.1109/CVPR.2012.6247772

Markdown

[Xu et al. "Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2012.](https://mlanthology.org/cvpr/2012/xu2012cvpr-multiple/) doi:10.1109/CVPR.2012.6247772

BibTeX

@inproceedings{xu2012cvpr-multiple,
  title     = {{Multiple Clustered Instance Learning for Histopathology Cancer Image Classification, Segmentation and Clustering}},
  author    = {Xu, Yan and Zhu, Jun-Yan and Chang, Eric I-Chao and Tu, Zhuowen},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2012},
  pages     = {964-971},
  doi       = {10.1109/CVPR.2012.6247772},
  url       = {https://mlanthology.org/cvpr/2012/xu2012cvpr-multiple/}
}