Dual-model automatic detection of nerve-fibres in corneal confocal microscopy images

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

Volumn 6361 LNCS, Issue PART 1, 2010, Pages 300-307

  Dabbah, M A ^a   Graham, J ^a   Petropoulos, I ^a   Tavakoli, M ^a   Malik, R A ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED METHODS; AUTOMATIC DETECTION; AUTOMATIC METHOD; CONTROL SUBJECT; DETECTION ALGORITHM; DIABETIC NEUROPATHY; DIABETIC PATIENT; ERROR RATE; FEATURE DETECTION; FIBRE LENGTH; GROUND TRUTH; NON-INVASIVE; PERIPHERAL NEUROPATHY; STRONG CORRELATION;

CONFOCAL MICROSCOPY; FIBERS; MATHEMATICAL MODELS; MEDICAL COMPUTING; SIGNAL TO NOISE RATIO;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; CONFOCAL MICROSCOPY; CORNEA; DIABETIC RETINOPATHY; HUMAN; IMAGE ENHANCEMENT; INNERVATION; METHODOLOGY; NERVE FIBER; OPHTHALMOSCOPY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CORNEA; DIABETIC RETINOPATHY; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MICROSCOPY, CONFOCAL; MODELS, BIOLOGICAL; NERVE FIBERS; OPHTHALMOSCOPY; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 80052142762     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15705-9_37     Document Type: Conference Paper

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