Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest

Medical Image Analysis

Volumn 24, Issue 1, 2015, Pages 77-89

  Xiong, Guanglei ^a   Kola, Deeksha ^b   Heo, Ran ^c   Elmore, Kimberly ^b   Cho, Iksung ^b   Min, James K ^b  

^a WEILL CORNELL MEDICAL COLLEGE   (United States)

^b NEW YORK PRESBYTERIAN HOSPITAL   (United States)

^c Yonsei University College of Medicine   (South Korea)

Author keywords

Computed tomography angiography; Coronary artery disease; Left ventricle segmentation; Perfusion analysis; Perfusion network; Rest perfusion

Indexed keywords

ADAPTIVE BOOSTING; ANGIOGRAPHY; COMPUTERIZED TOMOGRAPHY; DECISION TREES; DEFORMATION; DISEASES; IMAGE ACQUISITION; IMAGE ANALYSIS; LEARNING SYSTEMS; NONINVASIVE MEDICAL PROCEDURES;

COMPUTED TOMOGRAPHY ANGIOGRAPHY; CORONARY ARTERY DISEASE; LEFT VENTRICLES; PERFUSION ANALYSIS; REST PERFUSION;

HEART;

ADULT; ALGORITHM; ANATOMIC LANDMARK; ANGIOCARDIOGRAPHY; ARTICLE; BAYESIAN LEARNING; CARDIAC IMAGING; COMPUTED TOMOGRAPHIC ANGIOGRAPHY; COMPUTED TOMOGRAPHY SCANNER; CORONARY ARTERY OBSTRUCTION; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; ENDOCARDIUM; EPICARDIUM; FEMALE; HEART LEFT VENTRICLE; HEART MUSCLE PERFUSION; HEART VENTRICLE WALL; HUMAN; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; RANDOM FOREST; SENSITIVITY AND SPECIFICITY; VALIDATION STUDY; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; CORONARY ANGIOGRAPHY; DIAGNOSTIC IMAGING; IMAGE ENHANCEMENT; MACHINE LEARNING; MYOCARDIAL PERFUSION IMAGING; PROCEDURES; REPRODUCIBILITY; REST; X-RAY COMPUTED TOMOGRAPHY;

ALGORITHMS; CORONARY ANGIOGRAPHY; CORONARY STENOSIS; HUMANS; MACHINE LEARNING; MYOCARDIAL PERFUSION IMAGING; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; REST; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 84930933772     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2015.05.010     Document Type: Article

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