从腹部CT图像中提取肝脏和肿瘤

M. Jayanthi, B. Kanmani
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引用次数: 16

摘要

医学成像和计算机辅助诊断传统上侧重于基于器官或疾病的应用。CAD被放射科医生用作检测肿瘤、了解疾病程度和做出诊断决定的第二意见。由于CT图像中存在大小、形状、位置以及具有相同强度的其他物体,因此很难从CT图像中自动分割肿瘤。因此,首先要切除肝脏,这样才能准确地将肿瘤从肝脏中分离出来。本文提出了一种主要用于肝脏计算机辅助诊断的CT图像中肝脏和肿瘤的分割方法。该方法采用优化阈值算法进行区域增长。采用区域生长法,从种子点开始,自动检测并有效地封闭血管和肿瘤周围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extracting the Liver and Tumor from Abdominal CT Images
Medical imaging and computer aided diagnosis traditionally focus on organ or disease based applications. CAD is used by radiologists as a second opinion in detecting tumors, accessing the extent of diseases and making diagnostic decision. Automatic segmentation of tumor from CT images is difficult due to size, shape, position and presence of other objects with the same intensity present in the image. Therefore, first segment the liver so that tumor can then be segmented accurately from it. In this paper, an approach for segmentation of liver and tumor from CT Images is mainly used for computer aided diagnosis of liver is proposed. The method uses region growing with optimized threshold algorithm. The liver is segmented using region growing method that starts from a seed point automatically detected and efficiently close around the vessels and tumors.
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