虚拟结肠镜下结肠分割及清除混浊液的若干研究题目

G. Krishnamoorthy, B. Kishore
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引用次数: 0

摘要

结直肠癌(Colorectal cancer, CRC)是通过虚拟结肠镜(virtual colonoscopy, VC)在结肠或直肠中检测到的最重要的癌症类型,也是世界范围内普遍存在的主要死亡原因。CAD技术要求结肠的分割是准确的,可以通过两种方法实现。第一种方法侧重于使用聚类方法对从癌症成像档案(TCIA)下载的计算机断层扫描(CT)图像中的肺部进行分割。第二种方法是利用MATLAB对数据集中所有切片按顺序自动分割结肠、去除混浊液体和肠子。第二种方法需要更多的计算时间,因此,为了减少计算时间,在MEVISLAB软件中采用三维种子区域生长和模糊聚类方法实现冒号的半自动分割。这些方法在多个数据集中实施,并通过放射科医生手动分割验证了准确性,并表明去除混浊液体对于提高结肠段准确性的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Certain Investigation Titles on the Segmentation of Colon and Removal of Opacified Fluid for Virtual Colonoscopy
Colorectal cancer (CRC) is a most important type of cancer that can be detected by virtual colonoscopy (VC) in the colon or rectum, and it is the major cause of death prevailing in the world. The CAD technique requires the segmentation of the colon to be accurate and can be implemented by two approaches. The first approach focuses on the segmentation of lungs in the computed tomography (CT) images downloaded from The Cancer Imaging Archive (TCIA) using clustering approach. The second method focused on the automatic segmentation of colon, removal of opacified fluid and bowels for all the slices in a dataset in a sequential order using MATLAB. The second approach requires more computational time, and hence, in order to reduce, the semiautomatic segmentation of colon was implemented in 3D seeded region growing and fuzzy clustering approach in MEVISLAB software. The approaches were implemented in multiple datasets and the accuracy were verified with manual segmentation by radiologist, and the importance of removing opacified fluid were shown for improving the accuracy of colon segments.
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