CNN based Mitotic HEp-2 Cell Image Detection

Krati Gupta, Arnav Bhavsar, Anil K. Sao

Abstract

We propose a Convolutional Neural Network (CNN) framework to detect the individual mitotic HEp-2 cells against non-mitotic cells, which is important for Computer-Aided Detection (CAD) system for auto-immune disease diagnosis. The significant aspect of detecting mitotic HEp-2 cells is to consider the distinctive appearance differences between the mitotic and non-mitotic classes that are represented through the learned features from pre-trained CNN. We especially focus on gauging the effectiveness of learned features from different CNN layers, combined with traditional Support Vector Machine (SVM) classifier. We also consider the class sample skew between the classes. Importantly, we compare and discuss the performance of learned feature representations, and show that some of these features are indeed very effective in discriminating mitotic and non-mitotic cells. We demonstrate a high classification performance using the proposed framework.

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Paper Citation


in Harvard Style

Gupta K., Bhavsar A. and Sao A. (2018). CNN based Mitotic HEp-2 Cell Image Detection.In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING, ISBN 978-989-758-278-3, pages 167-174. DOI: 10.5220/0006721501670174


in Bibtex Style

@conference{bioimaging18,
author={Krati Gupta and Arnav Bhavsar and Anil K. Sao},
title={CNN based Mitotic HEp-2 Cell Image Detection},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING,},
year={2018},
pages={167-174},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006721501670174},
isbn={978-989-758-278-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING,
TI - CNN based Mitotic HEp-2 Cell Image Detection
SN - 978-989-758-278-3
AU - Gupta K.
AU - Bhavsar A.
AU - Sao A.
PY - 2018
SP - 167
EP - 174
DO - 10.5220/0006721501670174