Statistical detection of longitudinal changes between apparent diffusion coefficient images: Application to multiple sclerosis

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

Volumn 5761 LNCS, Issue PART 1, 2009, Pages 959-966

  Boisgontier, Hervé ^a   Noblet, Vincent ^a   Renard, Félix ^a   Heitz, Fabrice ^a   Rumbach, Lucien ^a,b   Armspach, Jean Paul ^a  

^a UNIVERSITÉ DE STRASBOURG   (France)

^b Service de Neurologie   (France)

Author keywords

[No Author keywords available]

Indexed keywords

APPARENT DIFFUSION COEFFICIENT; AUTOMATIC ANALYSIS; DIFFUSION PROPERTIES; DIFFUSION TENSOR IMAGING; EXISTING METHOD; FRACTIONAL ANISOTROPY; MEAN DIFFUSIVITY; MULTIPLE SCLEROSIS; MULTIPLE SCLEROSIS LESIONS; STATISTICAL DETECTION;

MEDICAL COMPUTING; STATISTICAL TESTS; SURFACE DIFFUSION;

TENSORS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; DIFFUSION WEIGHTED IMAGING; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; MULTIPLE SCLEROSIS; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS;

ALGORITHMS; BRAIN; DATA INTERPRETATION, STATISTICAL; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MULTIPLE SCLEROSIS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84859426319     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04268-3_118     Document Type: Conference Paper

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