Polyp Classification and Clustering from Endoscopic Images using Competitive and Convolutional Neural Networks

Avish Kabra; Yuji Iwahori; Hiroyasu Usami; M. K. Bhuyan; Naotaka Ogasawara; Kunio Kasugai

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Paper

Polyp Classification and Clustering from Endoscopic Images using Competitive and Convolutional Neural Networks

Topics: Deep Learning and Neural Networks; Image and Video Analysis and Understanding; Medical Imaging

In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 446-452, 2019 , Prague, Czech Republic

Authors: Avish Kabra ¹ ; Yuji Iwahori ² ; Hiroyasu Usami ² ; M. K. Bhuyan ¹ ; Naotaka Ogasawara ³ and Kunio Kasugai ³

Affiliations: ¹ Indian Institute of Technology Guwahati, Assam, 781039 and India ; ² Chubu University, 487-8501 and Japan ; ³ Aichi Medical University, 1-1 Yazakokarimata, Nagakute, Aichi, 480-1195 and Japan

Keyword(s): Competitive Learning, Deep Learning, Convolutional Neural Networks.

Related Ontology Subjects/Areas/Topics: Applications ; Medical Imaging ; Pattern Recognition ; Software Engineering

Abstract: Understanding the type of Polyp present in the body plays an important role in medical diagnosis. This paper proposes an approach to classify and cluster the polyp present in an Endoscopic scene into malignant or benign class. CNN and Self Organizing Maps are used to classify and cluster from white light and Narrow Band (NBI) Endoscopic Images . Using Competitive Neural Network different polyps available from previous data are plotted with the new polyp according to their structural similarity. Such kind of presentation not only help the doctor in it’s easy understanding but also helps him to know what kind of medical procedures were followed in similar cases.

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Paper citation in several formats:

Kabra, A.; Iwahori, Y.; Usami, H.; Bhuyan, M.; Ogasawara, N. and Kasugai, K. (2019). Polyp Classification and Clustering from Endoscopic Images using Competitive and Convolutional Neural Networks. In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-351-3; ISSN 2184-4313, SciTePress, pages 446-452. DOI: 10.5220/0007353204460452

@conference{icpram19,
author={Avish Kabra. and Yuji Iwahori. and Hiroyasu Usami. and M. K. Bhuyan. and Naotaka Ogasawara. and Kunio Kasugai.},
title={Polyp Classification and Clustering from Endoscopic Images using Competitive and Convolutional Neural Networks},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2019},
pages={446-452},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007353204460452},
isbn={978-989-758-351-3},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Polyp Classification and Clustering from Endoscopic Images using Competitive and Convolutional Neural Networks
SN - 978-989-758-351-3
IS - 2184-4313
AU - Kabra, A.
AU - Iwahori, Y.
AU - Usami, H.
AU - Bhuyan, M.
AU - Ogasawara, N.
AU - Kasugai, K.
PY - 2019
SP - 446
EP - 452
DO - 10.5220/0007353204460452
PB - SciTePress