Image-based respiratory motion compensation for fluoroscopic coronary roadmapping

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

Volumn 6363 LNCS, Issue PART 3, 2010, Pages 287-294

  Zhu, Ying ^a   Tsin, Yanghai ^a   Sundar, Hari ^a   Sauer, Frank ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLINICAL DATA; FLUOROSCOPIC IMAGES; IMAGE GRADIENTS; IMAGE-BASED; LARGE IMAGES; LUCAS-KANADE; MOTION MODELS; ROADMAPPING; SOFT TISSUE; STATIC STRUCTURES; TEMPORAL ANALYSIS; WEIGHTED SUM;

MEDICAL COMPUTING; MOTION COMPENSATION; RESPIRATORY MECHANICS;

MEDICAL IMAGING;

ALGORITHM; ANGIOCARDIOGRAPHY; ARTICLE; ARTIFACT; AUTOMATED PATTERN RECOGNITION; BREATHING MECHANICS; COMPUTER ASSISTED DIAGNOSIS; CORONARY ARTERY OBSTRUCTION; FLUOROSCOPY; HUMAN; IMAGE QUALITY; METHODOLOGY; MOVEMENT (PHYSIOLOGY); RADIOGRAPHY; REPRODUCIBILITY; RESPIRATORY GATED IMAGING; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFACTS; CORONARY ANGIOGRAPHY; CORONARY STENOSIS; FLUOROSCOPY; HUMANS; MOVEMENT; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; RESPIRATORY MECHANICS; RESPIRATORY-GATED IMAGING TECHNIQUES; SENSITIVITY AND SPECIFICITY;

EID: 84883837446     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15711-0_36     Document Type: Conference Paper

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