J Med Syst - Bleeding detection in Wireless Capsule Endoscopy based on Probabilistic Neural Network.

Tópicos

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Resumo

Wireless Capsule Endoscopy (WCE), which allows clinicians to inspect the whole gastrointestinal tract (GI) noninvasively, has bloomed into one of the most efficient technologies to diagnose the bleeding in GI tract. However WCE generates large amount of images in one examination of a patient. It is hard for clinicians to leave continuous time to examine the full WCE images, and this is the main factor limiting the wider application of WCE in clinic. A novel intelligent bleeding detection based on Probabilistic Neural Network (PNN) is proposed in this paper. The features of bleeding region in WCE images distinguishing from non-bleeding region are extracted. A PNN classifier is built to recognize bleeding regions in WCE images. Finally the intelligent bleeding detection method is implemented through programming. The experiments show this method can correctly recognize the bleeding regions in WCE images and clearly mark them out. The sensitivity and specificity on image level are measured as 93.1% and 85.6% respectively.

Resumo Limpo

wireless capsul endoscopi wce allow clinician inspect whole gastrointestin tract gi noninvas bloom one effici technolog diagnos bleed gi tract howev wce generat larg amount imag one examin patient hard clinician leav continu time examin full wce imag main factor limit wider applic wce clinic novel intellig bleed detect base probabilist neural network pnn propos paper featur bleed region wce imag distinguish nonbleed region extract pnn classifi built recogn bleed region wce imag final intellig bleed detect method implement program experi show method can correct recogn bleed region wce imag clear mark sensit specif imag level measur respect

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