Auto-Initialized Cascaded Level Set (AI-CALS) Segmentation of Bladder Lesions on Multidetector Row CT Urography

Academic Radiology

Volumn 20, Issue 2, 2013, Pages 148-155

  Hadjiiski, Lubomir ^a   Chan, Heang Ping ^a   Caoili, Elaine M ^a   Cohan, Richard H ^a   Wei, Jun ^a   Zhou, Chuan ^a  

^a UNIVERSITY OF MICHIGAN MEDICAL SCHOOL   (United States)

Author keywords

3D segmentation; Bladder cancer; CT urography; Level sets

Indexed keywords

NONIONIC CONTRAST MEDIUM;

ARTICLE; AUTOMATION; BENIGN TUMOR; BLADDER CANCER; BLADDER INJURY; BLADDER TUMOR; CANCER DIAGNOSIS; CLINICAL ARTICLE; COMPUTED TOMOGRAPHY UROGRAPHY; COMPUTER SYSTEM; CONTRAST ENHANCEMENT; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC IMAGING; DIAGNOSTIC TEST ACCURACY STUDY; GOLD STANDARD; HISTOGRAM; HUMAN; IMAGE QUALITY; INTERMETHOD COMPARISON; MULTIDETECTOR COMPUTED TOMOGRAPHY; PRIORITY JOURNAL; RADIOLOGIST; RATING SCALE; RETROSPECTIVE STUDY; THREE DIMENSIONAL IMAGING; UROGRAPHY;

ALGORITHMS; HUMANS; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED; URINARY BLADDER NEOPLASMS; UROGRAPHY;

EID: 84873523825     PISSN: 10766332     EISSN: 18784046     Source Type: Journal    
DOI: 10.1016/j.acra.2012.08.012     Document Type: Article

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