Autor(es):
Figueiredo, Pedro N. 
; Figueiredo, Isabel N. ; Prasath, Surya ; Tsai, Richard
Data: 2011
Identificador Persistente: http://hdl.handle.net/10316/15542
Origem: Estudo Geral - Universidade de Coimbra
Detalhes do Documento
Automatic Polyp Detection in Pillcam Colon 2 Capsule Images and Videos: Prelimi...
Descrição
Background. The aim of this work is to present an automatic colorectal polyp detection scheme for capsule endoscopy. Methods. PillCam COLON2 capsule-based images and videos were used in our study. The database consists of full exam videos from five patients. The algorithm is based on the assumption that the polyps show up as a protrusion in the captured images and is expressed bymeans of a P-value, defined by geometrical features. Results. Seventeen PillCamCOLON2 capsule videos are included, containing frames with polyps, flat lesions, diverticula, bubbles, and trash liquids. Polyps larger than 1 cmexpress a P-value higher than 2000, and 80% of the polyps show a P-value higher than 500. Diverticula, bubbles, trash liquids, and flat lesions were correctly interpreted by the algorithmas nonprotruding images. Conclusions. These preliminary results suggest that the proposed geometrybased polyp detection scheme works well, not only by allowing the detection of polyps but also by differentiating them from nonprotruding images found in the films.
Background. The aim of this work is to present an automatic colorectal polyp detection scheme for capsule endoscopy. Methods. PillCam COLON2 capsule-based images and videos were used in our study. The database consists of full exam videos from five patients. The algorithm is based on the assumption that the polyps show up as a protrusion in the captured images and is expressed bymeans of a P-value, defined by geometrical features. Results. Seventeen PillCamCOLON2 capsule videos are included, containing frames with polyps, flat lesions, diverticula, bubbles, and trash liquids. Polyps larger than 1 cmexpress a P-value higher than 2000, and 80% of the polyps show a P-value higher than 500. Diverticula, bubbles, trash liquids, and flat lesions were correctly interpreted by the algorithmas nonprotruding images. Conclusions. These preliminary results suggest that the proposed geometrybased polyp detection scheme works well, not only by allowing the detection of polyps but also by differentiating them from nonprotruding images found in the films.
Tipo de Documento
Artigo
Idioma Inglês
Idioma Inglês
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