Title :
Application of artificial neural networks for classification of colonoscopic images
Author :
Tjoa, M.P. ; Krishnan, M. ; Yap, J. ; Swaminathan, S. ; Wang, P.
Author_Institution :
BioMedical Eng. Res. Centre, Nanyang Technol. Univ., Singapore
Abstract :
Computer-aided methods in colonoscopy play an important role of assisting the physician in detecting abnormalities by characterizing the features of the segmented colonoscopic images. A novel image processing approach is proposed to extract the parametric features of the colonoscopic image. A comparison between two different types of neural networks, viz., the backpropagation (BP) and the adaptive resonance theory (ART) networks, is carried out to classify the status of the colon. The preliminary results obtained by the proposed methods are encouraging.
Keywords :
ART neural nets; backpropagation; biomedical optical imaging; cancer; feature extraction; image classification; medical image processing; tumours; ART networks; BP ANN; adaptive resonance theory networks; artificial neural networks; backpropagation ANN; colon abnormality detection; colon status classification; colonoscopic image classification; colonoscopy; colorectal cancer; computer-aided colonoscopy; image processing; parametric feature extraction; patient diagnosis; tumors; Application software; Artificial neural networks; Backpropagation; Colonoscopy; Feature extraction; Image processing; Image segmentation; Neural networks; Physics computing; Resonance;
Conference_Titel :
Circuits and Systems, 2002. APCCAS '02. 2002 Asia-Pacific Conference on
Print_ISBN :
0-7803-7690-0
DOI :
10.1109/APCCAS.2002.1115199
