3D automatic anatomy segmentation based on iterative graph-cut-ASM

Purpose: This paper studies the feasibility of developing an automatic anatomy segmentation (AAS) system in clinical radiology and demonstrates its operation on clinical 3D images.Methods: The AAS system, the authors are developing consists of two main parts: object recognition and object delineatio...

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Vydané v:	Medical physics (Lancaster) Ročník 38; číslo 8; s. 4610 - 4622
Hlavní autori:	Chen, Xinjian, Bagci, Ulas
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States American Association of Physicists in Medicine 01.08.2011
Predmet:	ABSORPTION SPECTROSCOPY ACCURACY active shape models ANATOMY Anatomy, Cross-Sectional - statistics & numerical data biomedical MRI Biophysical Phenomena bone CAT SCANNING Computed tomography computerised tomography Databases, Factual DATASETS EFFICIENCY FEET Female FEMALES Foot - anatomy & histology graph cut Humans IMAGE PROCESSING Image Processing, Computer-Assisted - statistics & numerical data image segmentation Imaging, Three-Dimensional - statistics & numerical data ITERATIVE METHODS kidney KIDNEYS LIVER Magnetic resonance imaging Magnetic Resonance Imaging - statistics & numerical data Male medical image processing Medical image segmentation Medical imaging Models, Anatomic NMR IMAGING Numerical approximation and analysis object recognition orthopaedics physiological models Probability theory, stochastic processes, and statistics Public address systems Radiation Imaging Physics Radiography, Abdominal - statistics & numerical data RADIOLOGY RADIOLOGY AND NUCLEAR MEDICINE ROTATION Segmentation Skin SPLEEN statistical analysis STATISTICAL MODELS TIBIA Tomography, X-Ray Computed - statistics & numerical data X‐ray imaging object recognition graph cut image segmentation active shape models statistical models
ISSN:	0094-2405, 2473-4209, 0094-2405
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