Your browser doesn't support javascript.
loading
Review: Segmentation and classification methods of 3D medical images / 中国医疗器械杂志
Article in Zh | WPRIM | ID: wpr-344254
Responsible library: WPRO
ABSTRACT
This paper presents a survey of recent publications (published in 1990 or later) concerning segmentation and classification of medical images. These methods will be classified into six types: cluster (threshold), statistics methods, deformable contour, region growing, mathematics morphology, nonlinear methods (fuzzy segmentation, neural networks, genetic algorithm) and 3D model. Each of the major classes of image segmentation and classification techniques and several specific examples of each class of algorithm are described respectively in detail. At last, the developing trend of 3D medical image is also discussed.
Subject(s)
Full text: 1 Index: WPRIM Main subject: Algorithms / Image Processing, Computer-Assisted / Artificial Intelligence / Cluster Analysis / Retrospective Studies / Models, Statistical / Information Storage and Retrieval / Neural Networks, Computer / Methods Type of study: Observational_studies / Risk_factors_studies Limits: Humans Language: Zh Journal: Chinese Journal of Medical Instrumentation Year: 2002 Type: Article
Full text: 1 Index: WPRIM Main subject: Algorithms / Image Processing, Computer-Assisted / Artificial Intelligence / Cluster Analysis / Retrospective Studies / Models, Statistical / Information Storage and Retrieval / Neural Networks, Computer / Methods Type of study: Observational_studies / Risk_factors_studies Limits: Humans Language: Zh Journal: Chinese Journal of Medical Instrumentation Year: 2002 Type: Article