Int J Comput Assist Radiol Surg - Toward embedded detection of polyps in WCE images for early diagnosis of colorectal cancer.

Tópicos

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Resumo

RPOSE: Wireless capsule endoscopy (WCE) is commonly used for noninvasive gastrointestinal tract evaluation, including the detection of mucosal polyps. A new embeddable method for polyp detection in wireless capsule endoscopic images was developed and tested.METHODS: First, possible polyps within the image were extracted using geometric shape features. Next, the candidate regions of interest were evaluated with a boosting based method using textural features. Each step was carefully chosen to accommodate hardware implementation constraints. The method's performance was evaluated on WCE datasets including 300 images with polyps and 1,200 images without polyps. Hardware implementation of the proposed approach was evaluated to quantitatively demonstrate the feasibility of such integration into the WCE itself.RESULTS: The boosting based polyp classification demonstrated a sensitivity of 91.0 %, a specificity of 95.2 % and a false detection rate of 4.8 %. This performance is close to that reported recently in systems developed for an online analysis of video colonoscopy images.CONCLUSION: A new method for polyp detection in videoendoscopic WCE examinations was developed using boosting based approach. This method achieved good classification performance and can be implemented in situ with embedded hardware.

Resumo Limpo

rpose wireless capsul endoscopi wce common use noninvas gastrointestin tract evalu includ detect mucos polyp new embedd method polyp detect wireless capsul endoscop imag develop testedmethod first possibl polyp within imag extract use geometr shape featur next candid region interest evalu boost base method use textur featur step care chosen accommod hardwar implement constraint method perform evalu wce dataset includ imag polyp imag without polyp hardwar implement propos approach evalu quantit demonstr feasibl integr wce itselfresult boost base polyp classif demonstr sensit specif fals detect rate perform close report recent system develop onlin analysi video colonoscopi imagesconclus new method polyp detect videoendoscop wce examin develop use boost base approach method achiev good classif perform can implement situ embed hardwar

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