Similarity guided feature labeling for lesion detection

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

Volumn 8149 LNCS, Issue PART 1, 2013, Pages 284-291

  Song, Yang ^a   Cai, Weidong ^a   Huang, Heng ^b   Wang, Xiaogang ^c   Eberl, Stefan ^d   Fulham, Michael ^d,e   Feng, Dagan ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

^b University of Texas at Arlington   (United States)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^d ROYAL PRINCE ALFRED HOSPITAL   (Australia)

^e UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ABNORMAL LYMPH NODES; ANATOMICAL STRUCTURES; CLASSIFICATION MODELS; FEATURE LABELING; FEATURE VARIATIONS; LESION DETECTION; SIMILARITY INFORMATIONS; SPARSE REPRESENTATION;

POSITRON EMISSION TOMOGRAPHY;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; MULTIMODAL IMAGING; NEOPLASM; POSITRON EMISSION TOMOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MULTIMODAL IMAGING; NEOPLASMS; PATTERN RECOGNITION, AUTOMATED; POSITRON-EMISSION TOMOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84885821175     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40811-3_36     Document Type: Conference Paper

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