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.
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Riaz, F., Vilarino, F., Ribeiro, M.D., Coimbra, M. (2011). Identifying Potentially Cancerous Tissues in Chromoendoscopy Images. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_88
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DOI: https://doi.org/10.1007/978-3-642-21257-4_88
Publisher Name: Springer, Berlin, Heidelberg
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