title: [Review: Segmentation and classification methods of 3D medical images].
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.
authors.affiliation: College of Biomedical Engineering and Instrumentation, Zhejiang University, Hangzhou, PR China.
authors.forename: Ou
authors.initials: O
authors.lastname: Tan
authors.forename: Hui-long
authors.initials: HL
authors.lastname: Duan
authors.forename: Wei-xue
authors.initials: WX
authors.lastname: Lu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D015233:Models, Statistical; D016571:Neural Networks, Computer; D012189:Retrospective Studies