Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models

Physics in Medicine and Biology

Volumn 57, Issue 24, 2012, Pages 8357-8376

  Neubert, A ^a,b   Fripp, J ^a   Engstrom, C ^b   Schwarz, R ^c   Lauer, L ^c   Salvado, O ^a   Crozier, S ^b  

^a CSIRO   (Australia)

^b UNIVERSITY OF QUEENSLAND   (Australia)

^c SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

3D SEGMENTATION; AUTOMATED APPROACH; AUTOMATED ASSESSMENT; AUTOMATED DETECTION; AUTOMATED SEGMENTATION; DATA SETS; DEGENERATIVE CHANGES; DISC DEGENERATION; GREY LEVELS; HIGH RESOLUTION; INTENSITY PROFILES; INTERVERTEBRAL DISCS; MANUAL SEGMENTATION; MORPHOLOGICAL INFORMATION; MR IMAGES; PRELIMINARY ANALYSIS; PULSE SEQUENCE; RADIOLOGICAL FINDINGS; SEGMENTATION TECHNIQUES; SHAPE PARAMETERS; STATISTICAL SHAPE ANALYSIS; STATISTICAL SHAPE MODEL; VERTEBRAL BODY; WEIGHTED SPACE;

AUTOMATION; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING; RADIOLOGY; THREE DIMENSIONAL COMPUTER GRAPHICS; VOLTAGE DIVIDERS;

THREE DIMENSIONAL;

ALGORITHM; ARTICLE; AUTOMATION; FEMALE; HUMAN; MALE; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; SPINE; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING; TIME;

ALGORITHMS; AUTOMATION; FEMALE; HUMANS; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MALE; MODELS, STATISTICAL; SPINE; TIME FACTORS;

EID: 84871191917     PISSN: 00319155     EISSN: 13616560     Source Type: Journal    
DOI: 10.1088/0031-9155/57/24/8357     Document Type: Article

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