IEEE J Biomed Health Inform - On the use of coupled shape priors for segmentation of magnetic resonance images of the knee.

Tópicos

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Resumo

Active contour techniques have been widely employed for medical image segmentation. Significant effort has been focused on the use of training data to build prior statistical models applicable specifically to problems where the objects of interest are embedded in cluttered background. Usually, the training data consist of whole shapes of certain organs or structures obtained manually by clinical experts. The resulting prior models enforce segmentation accuracy uniformly over the entire structure or structures to be identified. In this paper, we consider a new coupled prior shape model which is demonstrated to provide high accuracy, specifically in the region of the interest where precision is most needed for the application of the segmentation of the femur and tibia in magnetic resonance (MR) images. Experimental results for the segmentation of MR images of human knees demonstrate that the combination of the new coupled prior shape and a directional edge force provides the improved segmentation performance. Moreover, the new approach allows for equivalent accurate identification of bone marrow lesions, a promising biomarker related to osteoarthritis, to the current state of the art but requires significantly less manual interaction.

Resumo Limpo

activ contour techniqu wide employ medic imag segment signific effort focus use train data build prior statist model applic specif problem object interest embed clutter background usual train data consist whole shape certain organ structur obtain manual clinic expert result prior model enforc segment accuraci uniform entir structur structur identifi paper consid new coupl prior shape model demonstr provid high accuraci specif region interest precis need applic segment femur tibia magnet reson mr imag experiment result segment mr imag human knee demonstr combin new coupl prior shape direct edg forc provid improv segment perform moreov new approach allow equival accur identif bone marrow lesion promis biomark relat osteoarthr current state art requir signific less manual interact

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