Biomedical subjects
Publications and source records attributed to Ya-zhong Lin.
To propose an optimal level set approach for fast medical image segmentation. By confining the computation quantity of the level sets function and using the image characteristics, we improved the efficiency of segmentation and decreased the parameter setting in some degree for DSA vascular segmentation.
OBJECTIVE: To propose a new method for content-based retrieval from medical CT image database on the basis of automatically extracted features of the images. METHODS: An automatic feature extraction method is proposed based on expectation-maximization algorithm. A CT image is represented by a set of regions, each of which is characterized by a fuzzy regional feature vector reflecting the grey level, texture, shape, and the cumulative distribution histogram feature of the region of interest (ROI) to efficiently describe the difference between the ROIs. RESULTS: Compared with the submitted query image, the target images were retrieved in the order of similarity calculated by the proposed similarity measures. CONCLUSION: The proposed technique for CT image retrieval is suitable for clinical application, with greater precision and efficiency for retrieval than the conventional methods.