Comput. Biol. Med. - Segmentation of interest region in medical volume images using geometric deformable model.

Tópicos

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Resumo

In this paper, we present a new segmentation method using the level set framework for medical volume images. The method was implemented using the surface evolution principle based on the geometric deformable model and the level set theory. And, the speed function in the level set approach consists of a hybrid combination of three integral measures derived from the calculus of variation principle. The terms are defined as robust alignment, active region, and smoothing. These terms can help to obtain the precise surface of the target object and prevent the boundary leakage problem. The proposed method has been tested on synthetic and various medical volume images with normal tissue and tumor regions in order to evaluate its performance on visual and quantitative data. The quantitative validation of the proposed segmentation is shown with higher Jaccard's measure score (72.52%-94.17%) and lower Hausdorff distance (1.2654 mm-3.1527 mm) than the other methods such as mean speed (67.67%-93.36% and 1.3361mm-3.4463 mm), mean-variance speed (63.44%-94.72% and 1.3361 mm-3.4616 mm), and edge-based speed (0.76%-42.44% and 3.8010 mm-6.5389 mm). The experimental results confirm that the effectiveness and performance of our method is excellent compared with traditional approaches.

Resumo Limpo

paper present new segment method use level set framework medic volum imag method implement use surfac evolut principl base geometr deform model level set theori speed function level set approach consist hybrid combin three integr measur deriv calculus variat principl term defin robust align activ region smooth term can help obtain precis surfac target object prevent boundari leakag problem propos method test synthet various medic volum imag normal tissu tumor region order evalu perform visual quantit data quantit valid propos segment shown higher jaccard measur score lower hausdorff distanc mm mm method mean speed mm mm meanvari speed mm mm edgebas speed mm mm experiment result confirm effect perform method excel compar tradit approach

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