Identifying potentially cancerous tissues in chromoendoscopy images

Authors:
Farhan Riaz;Fernando Vilarino;Mario Dinis Ribeiro;Miguel Coimbra
Affiliations:
Instituto de Telecomunicacoes, Universidade do Porto and Computer Vision Center, Universitate Autnoma de Barcelona, Spain and Instituto Portugues Oncologia, Porto, Portugal;Instituto de Telecomunicacoes, Universidade do Porto and Computer Vision Center, Universitate Autnoma de Barcelona, Spain and Instituto Portugues Oncologia, Porto, Portugal;Instituto de Telecomunicacoes, Universidade do Porto and Computer Vision Center, Universitate Autnoma de Barcelona, Spain and Instituto Portugues Oncologia, Porto, Portugal;Instituto de Telecomunicacoes, Universidade do Porto and Computer Vision Center, Universitate Autnoma de Barcelona, Spain and Instituto Portugues Oncologia, Porto, Portugal
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

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Abstract

The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered.