Spatio-temporal signatures to predict retinal disease recurrence

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

Volumn 9123, Issue , 2015, Pages 152-163

  Vogl, Wolf Dieter ^a   Waldstein, Sebastian M ^a   Gerendas, Bianca S ^a   Simader, Christian ^a   Glodan, Ana Maria ^a   Podkowinski, Dominika ^a   Schmidt Erfurth, Ursula ^a   Langs, Georg ^a  

^a MEDICAL UNIVERSITY OF VIENNA   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

COHERENT LIGHT; FORECASTING; MEDICAL IMAGING; OPHTHALMOLOGY; OPTICAL TOMOGRAPHY; REGRESSION ANALYSIS;

GENERALIZED LINEAR MODEL; MEAN ABSOLUTE ERROR; MORPHOLOGY CHANGES; REFERENCE COORDINATE SYSTEM; RETINAL STRUCTURE; SPATIO TEMPORAL; SPECTRAL DOMAIN OPTICAL COHERENCE TOMOGRAPHIES; TREATMENT RESPONSE;

IMAGE PROCESSING;

MONOCLONAL ANTIBODY; RANIBIZUMAB;

ALGORITHM; COMPUTER ASSISTED DIAGNOSIS; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; OPTICAL COHERENCE TOMOGRAPHY; OUTCOME ASSESSMENT; PATHOLOGY; PROCEDURES; PROGNOSIS; RECURRENT DISEASE; REPRODUCIBILITY; RETINAL VEIN OCCLUSION; SENSITIVITY AND SPECIFICITY; SPATIOTEMPORAL ANALYSIS; TREATMENT OUTCOME;

ALGORITHMS; ANTIBODIES, MONOCLONAL, HUMANIZED; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATIENT OUTCOME ASSESSMENT; PROGNOSIS; RECURRENCE; REPRODUCIBILITY OF RESULTS; RETINAL VEIN OCCLUSION; SENSITIVITY AND SPECIFICITY; SPATIO-TEMPORAL ANALYSIS; SUBTRACTION TECHNIQUE; TOMOGRAPHY, OPTICAL COHERENCE; TREATMENT OUTCOME;

EID: 84942564344     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-19992-4_12     Document Type: Conference Paper

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