Comput Math Methods Med - Automatic segmentation of anatomical structures from CT scans of thorax for RTP.

Tópicos

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Resumo

Modern radiotherapy techniques are vulnerable to delineation inaccuracies owing to the steep dose gradient around the target. In this aspect, accurate contouring comprises an indispensable part of optimal radiation treatment planning (RTP). We suggest a fully automated method to segment the lungs, trachea/main bronchi, and spinal canal accurately from computed tomography (CT) scans of patients with lung cancer to use for RTP. For this purpose, we developed a new algorithm for inclusion of excluded pathological areas into the segmented lungs and a modified version of the fuzzy segmentation by morphological reconstruction for spinal canal segmentation and implemented some image processing algorithms along with them. To assess the accuracy, we performed two comparisons between the automatically obtained results and the results obtained manually by an expert. The average volume overlap ratio values range between 94.30 ? 3.93% and 99.11 ? 0.26% on the two different datasets. We obtained the average symmetric surface distance values between the ranges of 0.28 ? 0.21 mm and 0.89 ? 0.32 mm by using the same datasets. Our method provides favorable results in the segmentation of CT scans of patients with lung cancer and can avoid heavy computational load and might offer expedited segmentation that can be used in RTP.

Resumo Limpo

modern radiotherapi techniqu vulner delin inaccuraci owe steep dose gradient around target aspect accur contour compris indispens part optim radiat treatment plan rtp suggest fulli autom method segment lung tracheamain bronchi spinal canal accur comput tomographi ct scan patient lung cancer use rtp purpos develop new algorithm inclus exclud patholog area segment lung modifi version fuzzi segment morpholog reconstruct spinal canal segment implement imag process algorithm along assess accuraci perform two comparison automat obtain result result obtain manual expert averag volum overlap ratio valu rang two differ dataset obtain averag symmetr surfac distanc valu rang mm mm use dataset method provid favor result segment ct scan patient lung cancer can avoid heavi comput load might offer expedit segment can use rtp

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