Publication detail

Deep Learning Based Gastro Intestinal Disease Analysis Using Wireless Capsule Endoscopy Images

MALVIYA, A. SENGAR, N. DUTTA, M.K. BURGET, R. MYSKA, V.

Original Title

Deep Learning Based Gastro Intestinal Disease Analysis Using Wireless Capsule Endoscopy Images

Type

conference paper

Language

English

Original Abstract

Accurate detection of gastrointestinal illnesses is decisive for early cancer diagnosis and its treatment. However, manual analysis is time-consuming and requires a professional gastroenterologist. An efficient, robust and light-weight multi-class classification framework is proposed for screening different gastrointestinal diseases. A shallow neural network is developed that can extract the discriminative features by convolution of wireless capsule endoscopy (WCE) image even though the diseased images share common patterns. The network is optimised with various optimisation techniques to get the most optimised classification network. The proposed framework is capableof handling the challenges present in the dataset to improve the efficacy of the classification network. The network diagnoses unseen WCE image with 90% accuracy. The developed architecture is compared with other state-of-the-art networks and found to be highly efficient. The proposed network has the potential to perform better in limited computation and resource requirements.

Keywords

Artificial intelligence; Capsule endoscopy; Deep learning; Lesion detection

Authors

MALVIYA, A.; SENGAR, N.; DUTTA, M.K.; BURGET, R.; MYSKA, V.

Released

15. 8. 2022

Publisher

Institute of Electrical and Electronics Engineers Inc.

ISBN

9781665469487

Book

TSP 2022: 2022 45th International Conference on Telecommunications and Signal Processing

Pages from

221

Pages to

225

Pages count

5

URL

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9851383

BibTex

@inproceedings{BUT183058,
  author="MALVIYA, A. and SENGAR, N. and DUTTA, M.K. and BURGET, R. and MYSKA, V.",
  title="Deep Learning Based Gastro Intestinal Disease Analysis Using Wireless Capsule Endoscopy Images",
  booktitle="TSP 2022: 2022 45th International Conference on Telecommunications and Signal Processing",
  year="2022",
  pages="221--225",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  doi="10.1109/TSP55681.2022.9851383",
  isbn="9781665469487",
  url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9851383"
}