Knee cartilage: Efficient and reproducible segmentation on high-spatial-resolution MR images with the semiautomated graph-cut algorithm method

Radiology

Volumn 251, Issue 2, 2009, Pages 548-556

  Shim, Hackjoon ^a   Chang, Samuel ^a   Tao, Cheng ^a   Wang, Jin Hong ^a   Kwoh, C Kent ^a,b   Bae, Kyongtae T ^a  

^a UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE   (United States)

^b VETERANS AFFAIRS MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTICULAR CARTILAGE; AUTOMATION; HUMAN; IMAGE PROCESSING; IMAGE QUALITY; KNEE OSTEOARTHRITIS; KNEE RADIOGRAPHY; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; PROSPECTIVE STUDY; RADIOLOGIST; RELIABILITY; REPRODUCIBILITY; STEADY STATE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; KNEE; METHODOLOGY; PATHOLOGY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CARTILAGE, ARTICULAR; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; KNEE JOINT; MAGNETIC RESONANCE IMAGING; OSTEOARTHRITIS, KNEE; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 66149116027     PISSN: 00338419     EISSN: 15271315     Source Type: Journal    
DOI: 10.1148/radiol.2512081332     Document Type: Article

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