Synthetic ground truth for validation of brain tumor MRI segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3749 LNCS, Issue , 2005, Pages 26-33

  Prastawa, Marcel ^a   Bullitt, Elizabeth ^b   Gerig, Guido ^a,b  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMECHANICS; BRAIN; DIFFUSION; MAGNETIC RESONANCE IMAGING; PATHOLOGY; TENSORS; TUMORS;

BIOMECHANICAL MODELS; BRAIN TUMOR; DIFFUSION TENSORS; MRI SEGMENTATION;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BRAIN TUMOR; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN NEOPLASMS; DIAGNOSIS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; METHODS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE VALIDATION;

EID: 33744825479     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11566465_4     Document Type: Conference Paper

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