An Automatic Kidney Segmentation from Abdominal CT Images
The problem we address in this paper is the automatic kidney segmentation from abdominal 2D computed tomography images (CT). Accurately identifying kidney in medical image is a key step relating to the study of various kidney diseases. However, kidney segmentation from CT images is generally performed manually or semi-automatically because of gray levels similarities of adjacent organs, contrast media effect and relatively high variation of organs positions and shapes in abdominal CT images. The proposed method in this paper is the combination of medical anatomic knowledge and image processing methods a which can be divided into two stages. First, an improved connected component labeling algorithm based on intensity value is proposed to extract estimated kidney position (EKP). This algorithm is applicable to abdominal CT images of different sizes by using the position of kidney and spine. In the second stage, a novel region growing approach based on multi-scale mathematical morphology and labeling algorithm is used to extract the fine kidney regions. The method is tested on over 200 clinically acquired images and very promising results were obtained.
Abdominal CT images Kidney segmentation estimated kidney position (EKP) region growing
Gao yan boliang Wang
Department of Cognitive Science Xiamen University Xiamen, China Department of Computer Science Xiamen University Xiamen, China
国际会议
厦门
英文
280-284
2010-10-29（万方平台首次上网日期，不代表论文的发表时间）