Multiple abdominal organ segmentation: an atlas-based fuzzy connectedness approach.
Organ segmentation is an important step in various medical image applications. In this paper, a presegmented atlas is incorporated into the fuzzy connectedness (FC) framework for automatic segmentation of abdominal organs. First, the atlas is registered onto the subject to provide an initial segmentation. Then, a novel method is applied to estimate the necessary FC parameters such as organ intensity features, seeds, and optimal FC threshold automatically and subject adaptively. In order to overcome the intensity overlapping between the neighboring organs, a shape modification approach based on Euclidean distance and watershed segmentation is used. This atlas-based segmentation method has been tested on some abdominal CT and MRI images from Chinese patients. Experimental results indicate the validity of this segmentation method for various image modalities.
Zhou
Yongxin
Y
Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China. zhouyongxin@tsinghua.edu.cn
Bai
Jing
J
D000005:Abdomen / Q000033:anatomy & histology; D000465:Algorithms; D001185:Artificial Intelligence; D017143:Fuzzy Logic; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods; D008488:Medical Illustration; D008953:Models, Anatomic; D010363:Pattern Recognition, Automated / Q000379:methods*; D011860:Radiography, Abdominal / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods; D014781:Viscera / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*