Magnetic resonance angiography: From anatomical knowledge modeling to vessel segmentation

Medical Image Analysis

Volumn 10, Issue 2, 2006, Pages 259-274

  Passat, N ^a,b   Ronse, C ^a   Baruthio, J ^b   Armspach, J P ^b   Maillot, C ^c  

^a Faculté de Médecine   (France)

^b CNRS   (France)

^c UNIVERSITÉ DE STRASBOURG   (France)

Author keywords

Anatomical knowledge modeling; Brain vessel segmentation; Magnetic resonance angiography; Mathematical morphology

Indexed keywords

ALGORITHMS; BLOOD; BRAIN; DATABASE SYSTEMS; IMAGE SEGMENTATION; MATHEMATICAL MORPHOLOGY; NEUROSURGERY; PATHOLOGY; TOPOLOGY;

ANATOMICAL KNOWLEDGE MODELING; BRAIN VESSEL SEGMENTATION; MAGNETIC RESONANCE ANGIOGRAPHY;

ANGIOGRAPHY;

ALGORITHM; ARTICLE; BRAIN BLOOD FLOW; BRAIN BLOOD VESSEL; BRAIN FUNCTION; CEREBROVASCULAR DISEASE; CONTRAST ENHANCEMENT; DATA BASE; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; FUNCTIONAL ASSESSMENT; HUMAN; IMAGE ANALYSIS; INFORMATION RETRIEVAL; INTERMETHOD COMPARISON; MAGNETIC RESONANCE ANGIOGRAPHY; MATHEMATICAL MODEL; METHODOLOGY; NEUROIMAGING; NEUROSURGERY; NON INVASIVE MEASUREMENT; PATHOLOGICAL ANATOMY; PRIORITY JOURNAL; SURGICAL ANATOMY; TREATMENT PLANNING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CEREBRAL ARTERIES; COMPUTER SIMULATION; DATABASES, FACTUAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE ANGIOGRAPHY; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 31744435697     PISSN: 13618415     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.media.2005.11.002     Document Type: Article

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