title: Compressed domain topographic classification for capsule endoscopy.
abstract: In this paper we compare the classification accuracy of using compressed domain color (CDC) descriptors versus traditional full decoded images, for the purposes of topographic classification of wireless capsule endoscopy images. Results using a dataset of 26469 images, divided into stomach, small intestine and large intestine show a difference in classification accuracy below 1%. We also show that errors are mostly located near zone transitions (the pylorus and the ileocecal valve) and motivate the need for other visual descriptors (e.g. shape, motion) for addressing these specific areas. We conclude we can use the advantages of CDC in this type of classification with minor accuracy sacrifice.
authors.affiliation: Department of Computer Science, Faculdade de Ciências, Instituto de Telecomunicações, Universidade do Porto, Portugal. nunomarques@dcc.fc.up.pt
authors.forename: N
authors.initials: N
authors.lastname: Marques
authors.forename: E
authors.initials: E
authors.lastname: Dias
authors.forename: J P S
authors.initials: JP
authors.lastname: Cunha
authors.forename: M
authors.initials: M
authors.lastname: Coimbra
mesh_terms: D053704:Capsule Endoscopy / Q000379:methods*; D003116:Color; D001330:Electronic Data Processing; D019723:Endoscopes; D004867:Equipment Design; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted; D007420:Intestine, Large / Q000473:pathology; D007421:Intestine, Small / Q000473:pathology*; D015233:Models, Statistical; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D013270:Stomach / Q000473:pathology