Int J Comput Assist Radiol Surg - Segmentation of bones in magnetic resonance images of the wrist.

Tópicos

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Resumo

RPOSE: Rheumatoid arthritis (RA) is a disease characterized by progressive and irreversible destruction of bones and joints. According to current recommendations, magnetic resonance imaging (MRI) is used to asses three main signs of RA based on manual evaluation of MR images: synovitis, bone edema and bone erosions. The key feature of a future computer-assisted diagnostic system for evaluation RA lesions is accurate segmentation of 15 wrist bones. In the present paper, we focus on developing a wrist bones segmentation framework.METHOD: The segmentation procedure consisted of three stages: segmentation of the distal parts of ulna and radius, segmentation of the proximal parts of metacarpal bones and segmentation of carpal bones. At every stage, markers of bones were determined first, using an atlas-based approach. Then, given markers of bones and a marker of background, a watershed from markers algorithm was applied to find the final segmentation.RESULTS: The MR data for 37 cases were analyzed. The automated segmentation results were compared with gold-standard manual segmentations using a few well-established metrics: area under ROC curve AUC, mean similarity MS and mean absolute distance MAD. The mean (standard deviation) values of AUC, MS and MAD were 0.97 (0.04), 0.93 (0.09) and 1.23 (0.28), respectively.CONCLUSION: The results of the present study demonstrate that automated segmentation of wrist bones is feasible. The proposed algorithm can be the first stage for the detection of early lesions like bone edema or synovitis.

Resumo Limpo

rpose rheumatoid arthriti ra diseas character progress irrevers destruct bone joint accord current recommend magnet reson imag mri use ass three main sign ra base manual evalu mr imag synov bone edema bone eros key featur futur computerassist diagnost system evalu ra lesion accur segment wrist bone present paper focus develop wrist bone segment frameworkmethod segment procedur consist three stage segment distal part ulna radius segment proxim part metacarp bone segment carpal bone everi stage marker bone determin first use atlasbas approach given marker bone marker background watersh marker algorithm appli find final segmentationresult mr data case analyz autom segment result compar goldstandard manual segment use wellestablish metric area roc curv auc mean similar ms mean absolut distanc mad mean standard deviat valu auc ms mad respectivelyconclus result present studi demonstr autom segment wrist bone feasibl propos algorithm can first stage detect earli lesion like bone edema synov

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