Kamiya N, Zhou X, Chen H, Hara T, Hoshi H, Yokoyama R, Kanematsu M, Fujita H
Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, Yanagido 1-1, Gifu 501-1194, Japan.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3557-60. doi: 10.1109/IEMBS.2009.5332597.
The purpose of this study is to recognize the psoas major muscle on X-ray CT images. For this purpose, we propose a novel recognition method. The recognition process in this method involves three steps: the generation of a shape model for the psoas major muscle, recognition of anatomical points such as the origin and insertion, and the recognition of the psoas major muscles by the use of the shape model. We generated the shape model using 20 CT cases and tested the model for recognition in 20 other CT cases. The average Jaccard similarity coefficient (JSC) and reproducibility rate were 0.704 and 0.783, respectively. Experimental results indicate that our method was effective for a 2-D cross-sectional area (CSA) analysis.
本研究的目的是在X射线CT图像上识别腰大肌。为此，我们提出了一种新颖的识别方法。该方法的识别过程包括三个步骤：生成腰大肌的形状模型、识别诸如起点和止点等解剖学点，以及使用形状模型识别腰大肌。我们使用20例CT病例生成了形状模型，并在另外20例CT病例中测试了该模型的识别能力。平均杰卡德相似系数（JSC）和重现率分别为0.704和0.783。实验结果表明，我们的方法对于二维横截面积（CSA）分析是有效的。
