Synthetic MRI signal standardization: Application to multi-atlas analysis

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 81-88

  Iglesias, Juan Eugenio ^a   Dinov, Ivo ^a   Singh, Jaskaran ^a   Tong, Gregory ^a   Tu, Zhuowen ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; IMAGE ANALYSIS; MEDICAL COMPUTING; MEDICAL IMAGING; SIGNAL SYSTEMS; STANDARDIZATION;

ACQUISITION PARAMETERS; BRAIN REGIONS; COIL SENSITIVITY; CORRECTION METHOD; DATA SETS; GOLD STANDARDS; GRAY LEVELS; HIPPOCAMPUS SEGMENTATION; IMAGE ANALYSIS TECHNIQUES; IMAGE INTENSITIES; INTENSITY DISTRIBUTION; MRI SCAN; MULTI-SPECTRAL DATA; PHYSICAL MODEL; PULSE SEQUENCE; TISSUE PROPERTIES;

MAGNETIC RESONANCE IMAGING;

ALGORITHM; ARTICLE; AUDIOVISUAL EQUIPMENT; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ANATOMY AND HISTOLOGY; BRAIN; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; METHODS; MODELS, ANATOMIC; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 78349259285     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15711-0_11     Document Type: Conference Paper

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