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High-Magnification Multi-Views Based Classification of Breast Fine Needle Aspiration Cytology Cell Samples Using Fusion of Decisions from Deep Convolutional Networks

Hrushikesh Garud, Sri Phani Krishna Karri, Debdoot Sheet, Jyotirmoy Chatterjee, Manjunatha Mahadevappa, Ajoy Kumar Ray, Arindam Ghosh, Ashok K. Maity
CVPRW 2017 pp. 828-833
doi:10.1109/CVPRW.2017.115 /cvprw/2017/garud2017cvprw-highmagnification/

Abstract

Fine needle aspiration cytology is commonly used for diagnosis of breast cancer, with traditional practice being based on the subjective visual assessment of the breast cytopathology cell samples under a microscope to evaluate the state of various cytological features. Therefore, there are many challenges in maintaining consistency and reproducibility of findings. However, digital imaging and computational aid in diagnosis can improve the diagnostic accuracy and reduce the effective workload of pathologists. This paper presents a deep convolutional neural network (CNN) based classification approach for the diagnosis of the cell samples using their microscopic high-magnification multi-views. The proposed approach has been tested using GoogLeNet architecture of CNN on an image dataset of 37 breast cytopathology samples (24 benign and 13 malignant), where the network was trained using images of ~54% cell samples and tested on the rest, achieving 89.7% mean accuracy in 8 fold validation.

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Cite

Text

Garud et al. "High-Magnification Multi-Views Based Classification of Breast Fine Needle Aspiration Cytology Cell Samples Using Fusion of Decisions from Deep Convolutional Networks." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017. doi:10.1109/CVPRW.2017.115

Markdown

[Garud et al. "High-Magnification Multi-Views Based Classification of Breast Fine Needle Aspiration Cytology Cell Samples Using Fusion of Decisions from Deep Convolutional Networks." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2017.](https://mlanthology.org/cvprw/2017/garud2017cvprw-highmagnification/) doi:10.1109/CVPRW.2017.115

BibTeX

@inproceedings{garud2017cvprw-highmagnification,
  title     = {{High-Magnification Multi-Views Based Classification of Breast Fine Needle Aspiration Cytology Cell Samples Using Fusion of Decisions from Deep Convolutional Networks}},
  author    = {Garud, Hrushikesh and Karri, Sri Phani Krishna and Sheet, Debdoot and Chatterjee, Jyotirmoy and Mahadevappa, Manjunatha and Ray, Ajoy Kumar and Ghosh, Arindam and Maity, Ashok K.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2017},
  pages     = {828-833},
  doi       = {10.1109/CVPRW.2017.115},
  url       = {https://mlanthology.org/cvprw/2017/garud2017cvprw-highmagnification/}
}