Robust learning-based parsing and annotation of medical radiographs

IEEE Transactions on Medical Imaging

Volumn 30, Issue 2, 2011, Pages 338-350

  Tao, Yimo ^a   Peng, Zhigang ^b   Krishnan, Arun ^b   Zhou, Xiang Sean ^b  

^a Microsoft Health Solutions Group   (United States)

^b SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

Chest radiograph; hanging protocol; medical image annotation; object recognition; picture archive and communication system (PACS)

Indexed keywords

AUTOMATIC MEDICAL IMAGE ANNOTATION; CHEST IMAGE; CHEST RADIOGRAPHS; COMPUTER AIDED DETECTION; FINAL DECISION; HANGING PROTOCOLS; IMAGE PARSING; IMAGE VISUALIZATION; IMAGING ARTIFACTS; LEARNING-BASED ALGORITHMS; MEDICAL IMAGE ANNOTATION; MISSING DATA; MULTI-CLASS; PICTURE ARCHIVE AND COMMUNICATION SYSTEM (PACS); POSITION IDENTIFICATION; REGION OF INTEREST; ROBUST AGGREGATION; ROBUST LEARNING; SPATIAL CONFIGURATION; STATE-OF-THE-ART ALGORITHMS; WORK-FLOWS;

ALGORITHMS; COMMUNICATION SYSTEMS; DETECTORS; IMAGE ANALYSIS; IMAGE SEGMENTATION; OBJECT RECOGNITION; RADIOGRAPHY; VISUALIZATION;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL INTELLIGENCE; HUMAN; IMAGE PROCESSING; METHODOLOGY; RADIOGRAPHY;

ALGORITHMS; ARTIFACTS; ARTIFICIAL INTELLIGENCE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; RADIOGRAPHY;

EID: 79551607567     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2010.2077740     Document Type: Article

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