Registration accuracy: How good is good enough? a statistical power calculation incorporating image registration uncertainty

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

Volumn 7511 LNCS, Issue , 2012, Pages 643-650

  Gibson, Eli ^a   Fenster, Aaron ^a,b,c   Ward, Aaron D ^b,c  

^a ROBARTS RESEARCH INSTITUTE   (Canada)

^b LAWSON HEALTH RESEARCH INSTITUTE   (Canada)

^c UNIVERSITY OF WESTERN ONTARIO   (Canada)

Author keywords

Imaging validation; Registration error; Statistical power

Indexed keywords

ERRORS; IMAGE REGISTRATION; INTELLIGENT SYSTEMS; MEDICAL COMPUTING; MONTE CARLO METHODS; STATISTICS;

MINIMUM DETECTABLE DIFFERENCES; POWER CALCULATION; REGISTRATION ACCURACY; REGISTRATION ERROR; SAMPLE SIZES; STATISTICAL POWER; TARGET REGISTRATION ERRORS; VALIDATION STUDY;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS;

ALGORITHMS; DATA INTERPRETATION, STATISTICAL; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84872899910     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33418-4_79     Document Type: Conference Paper

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