Automatic segmentation of magnetic resonance images using a decision tree with spatial information

Computerized Medical Imaging and Graphics

Volumn 33, Issue 2, 2009, Pages 111-121

  Chao, Wen Hung ^a,b   Chen, You Yin ^a   Lin, Sheng Huang ^c   Shih, Yen Yu I ^d   Tsang, Siny ^e  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

^b YUANPEI UNIVERSITY   (Taiwan)

^c BUDDHIST TZU CHI GENERAL HOSPITAL   (Taiwan)

^d INSTITUTE OF BIOMEDICAL SCIENCES   (Taiwan)

^e SAM HOUSTON STATE UNIVERSITY   (United States)

Author keywords

Accuracy rates; Automatic segmentation; Decision tree; Spatial information; Wavelet transform

Indexed keywords

ACCURACY RATES; ANATOMICAL STRUCTURES; AUTOMATIC DECISIONS; AUTOMATIC SEGMENTATION; BOUNDARY DETECTIONS; BRAIN TISSUES; COORDINATE SYSTEMS; DECISION TREE ALGORITHMS; DIMENSIONAL WAVELET TRANSFORMS; EUCLIDEAN COORDINATES; GRAY LEVELS; GRAY MATTERS; HAUSDORFF DISTANCES; INPUT FEATURES; MAGNETIC RESONANCE IMAGES; MR IMAGES; NOISE LEVELS; NOISE VARIATIONS; PHANTOM IMAGES; POLAR COORDINATES; SEGMENTATION METHODS; SIMULATED PHANTOMS; SPATIAL INFORMATION; TWO TYPES; WHITE MATTERS;

ACOUSTIC NOISE; ATOMS; BINARY TREES; DATA STRUCTURES; DECISION THEORY; DECISION TREES; FILE ORGANIZATION; GRANULAR MATERIALS; IMAGE ENHANCEMENT; IMAGE REGISTRATION; IMAGE SEGMENTATION; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; RESONANCE; WAVELET TRANSFORMS;

TREES (MATHEMATICS);

ALGORITHM; ANATOMY; ARTICLE; AUTOMATION; BRAIN TISSUE; CLINICAL EVALUATION; COMPUTER; DECISION TREE; DIAGNOSTIC ACCURACY; GRAY MATTER; HUMAN; IMAGE ANALYSIS; INFORMATION PROCESSING; METHODOLOGY; NEUROIMAGING; NOISE; NONHUMAN; NUCLEAR MAGNETIC RESONANCE IMAGING; PERFORMANCE; PHANTOM; PRIORITY JOURNAL; WHITE MATTER;

ARTIFACTS; ARTIFICIAL INTELLIGENCE; BRAIN; COMPUTER SIMULATION; DECISION TREES; HUMANS; IMAGE ENHANCEMENT; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; PHANTOMS, IMAGING; REFERENCE VALUES; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 58149236665     PISSN: 08956111     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2008.10.008     Document Type: Article

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