Comput Math Methods Med - A hybrid method for pancreas extraction from CT image based on level set methods.

Tópicos

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Resumo

This paper proposes a novel semiautomatic method to extract the pancreas from abdominal CT images. Traditional level set and region growing methods that request locating initial contour near the final boundary of object have problem of leakage to nearby tissues of pancreas region. The proposed method consists of a customized fast-marching level set method which generates an optimal initial pancreas region to solve the problem that the level set method is sensitive to the initial contour location and a modified distance regularized level set method which extracts accurate pancreas. The novelty in our method is the proper selection and combination of level set methods, furthermore an energy-decrement algorithm and an energy-tune algorithm are proposed to reduce the negative impact of bonding force caused by connected tissue whose intensity is similar with pancreas. As a result, our method overcomes the shortages of oversegmentation at weak boundary and can accurately extract pancreas from CT images. The proposed method is compared to other five state-of-the-art medical image segmentation methods based on a CT image dataset which contains abdominal images from 10 patients. The evaluated results demonstrate that our method outperforms other methods by achieving higher accuracy and making less false segmentation in pancreas extraction.

Resumo Limpo

paper propos novel semiautomat method extract pancrea abdomin ct imag tradit level set region grow method request locat initi contour near final boundari object problem leakag nearbi tissu pancrea region propos method consist custom fastmarch level set method generat optim initi pancrea region solv problem level set method sensit initi contour locat modifi distanc regular level set method extract accur pancrea novelti method proper select combin level set method furthermor energydecr algorithm energytun algorithm propos reduc negat impact bond forc caus connect tissu whose intens similar pancrea result method overcom shortag oversegment weak boundari can accur extract pancrea ct imag propos method compar five stateoftheart medic imag segment method base ct imag dataset contain abdomin imag patient evalu result demonstr method outperform method achiev higher accuraci make less fals segment pancrea extract

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