Tumor recognition in endoscopic video images using artificial neural network architectures

Karkanis, S.A. and Iakovidis, D.K. and Maroulis, D.E. and Theofanous, N.G. and Magoulas, George (2000) Tumor recognition in endoscopic video images using artificial neural network architectures. In: UNSPECIFIED (ed.) 26th EUROMICRO 2000 Conference, Informatics: Inventing the Future. IEEE Computer Society. ISBN 0769507808.

Full text not available from this repository.

Official URL: https://doi.org/10.1109/EURMIC.2000.874524

Abstract

The paper focuses on a scheme for automated tumor recognition using images acquired during endoscopic sessions. The proposed recognition system is based on multilayer feed forward neural networks (MFNNs) and uses texture information encoded with corresponding statistical measures that are fed as input to the MFNN. Experiments were performed for recognition of different types of tumors in various images and also a number of sequentially acquired frames. The recognition of a polypoid tumor of the colon in the original image, which were used for training was very high. The trained network was also able to satisfactorily recognize the tumor in a sequence of video frames. The results of the proposed approach were very promising and it seems that it can be efficiently applied for tumor recognition.

Metadata

Item Type:	Book Section
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Sarah Hall
Date Deposited:	06 Jul 2021 11:07
Last Modified:	09 Aug 2023 12:51
URI:	https://eprints.bbk.ac.uk/id/eprint/44995

Statistics

Archive Staff Only (login required)

Edit/View Item