Liver tumour segmentation using contrast-enhanced multi-detector CT data: Performance benchmarking of three semiautomated methods

European Radiology

Volumn 20, Issue 7, 2010, Pages 1738-1748

  Zhou, Jia Yin ^a,b   Wong, Damon W K ^b   Ding, Feng ^a   Venkatesh, Sudhakar K ^a   Tian, Qi ^b   Qi, Ying Yi ^a   Xiong, Wei ^b   Liu, Jimmy J ^b   Leow, Wee Kheng ^c  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^c NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Computed tomography (CT); Image segmentation; Liver tumour; Performance benchmarking; Tumour volumetry

Indexed keywords

ARTICLE; BAYESIAN LEARNING; CLASSIFICATION ALGORITHM; CONTRAST ENHANCEMENT; HUMAN; HUMAN TISSUE; LIVER TUMOR; MULTIDETECTOR COMPUTED TOMOGRAPHY; PRIORITY JOURNAL; QUALITY CONTROL; TUMOR VOLUMETRY; VOLUMETRY; ALGORITHM; AUTOMATION; CANCER STAGING; COMPUTER ASSISTED TOMOGRAPHY; IMAGE PROCESSING; PATHOLOGY; PROCEDURES; RADIOGRAPHY; STANDARD; TUMOR VOLUME;

ALGORITHMS; AUTOMATION; BENCHMARKING; CONTRAST MEDIA; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LIVER NEOPLASMS; NEOPLASM STAGING; REFERENCE STANDARDS; TOMOGRAPHY, X-RAY COMPUTED; TUMOR BURDEN;

CONTRAST MEDIUM;

EID: 77954819248     PISSN: 09387994     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00330-010-1712-z     Document Type: Article

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