The usage of soft-computing methodologies in interpreting capsule endoscopy

Authors:
V. S. Kodogiannis;M. Boulougoura;E. Wadge;J. N. Lygouras
Affiliations:
Centre for Systems Analysis, School of Computer Science, University of Westminster, London, HA1 3TP, UK;IBM Hellas S.A., 284 Kifissias Ave, Athens, GR-15232, Greece;Centre for Systems Analysis, School of Computer Science, University of Westminster, London, HA1 3TP, UK;Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi GR-67100, Greece
Venue:
Engineering Applications of Artificial Intelligence
Year:
2007

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Capsule endoscopy image analysis using texture information from various colour models

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Abstract

Computerised processing of medical images can ease the search of the representative features in the images. The endoscopic images possess rich information expressed by texture and regions affected by diseases, such as ulcer or coli, may have different texture features. In this paper schemes have been developed to extract features from the texture spectra in the chromatic and achromatic domains for a selected region of interest from each colour component histogram of images acquired by the M2A Swallowable Imaging Capsule. The implementation of neural network schemes and the concept of fusion of multiple classifiers have been also adopted in this paper. The preliminary test results support the feasibility of the proposed method.