体格正規化手法と個別尤度マップを用いた3次元腹部CT像からの複数臓器抽出手法に関する検討

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  • タイカク セイキカ シュホウ ト コベツ ユウド マップ オ モチイタ 3ジゲン フクブ CTゾウ カラ ノ フクスウ ゾウキ チュウシュツ シュホウ ニ カンスル ケントウ
  • A Study on Multiple Organ Segmentation from 3D CT Images Based on Normalization Method and Patient-Specific Probabilistic Map

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Organ segmentation from 3D abdominal CT database is a difficult process due to the large differences among patients in organ size and location. It is necessary to normalize physical size for each CT data in the database if CT database is utilized for organ segmentation. In this paper, we propose a new normalization method on physical size. Also, we incorporate it into a patient-specific atlas based method for multi-organ segmentation. Firstly, we roughly extract lung and kidney areas to normalize the physical sizes of the CT images in database. We dynamically generate a patient-specific probabilistic atlas for each new target image by using the normalized CT database. We roughly segment the organ region based on the probabilistic atlas and refine it by using a graph-cuts method. Experimental results showed that our approach can segment the liver, the spleen, the pancreas, and the kidney correctly with Jaccard indices of 95.1%, 91.4%, 69.1%, and 90.1%, respectively.

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