Classification of SD-OCT Volumes Using Local Binary Patterns: Experimental Validation for DME Detection

Autor: Désiré Sidibé, Ecosse L. Lamoureux, Fabrice Meriaudeau, Guillaume Lemaitre, Carol Y. Cheung, Joan Massich, Dan Milea, Mojdeh Rastgoo, Tien Yin Wong
Přispěvatelé: Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Department of Ophthalmology and Visual Science, The Chinese University of Hong Kong [Hong Kong], Singapore Eye Research Institute, Singapore National Eye Centre, Centre for Intelligent Signal and Imaging Research (Universiti Teknologi Petronas) ( CISIR ), Singapore French Institute (IFS), Singapore Eye Research Institute (SERI), Regional Council of Burgundy 2015-9201AAO050S02760, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Centre for Intelligent Signal and Imaging Research [Petronas] (CISIR), Universiti Teknologi PETRONAS (UTP), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Lemaitre, Guillaume
Jazyk: angličtina
Rok vydání: 2016
Předmět:
genetic structures
[INFO.INFO-IM] Computer Science [cs]/Medical Imaging
[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing
[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
0302 clinical medicine
[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Segmentation
lcsh:Ophthalmology
Speckle
LBP
Diagnosis
Prevalence
Preprocessor
Computer vision
medicine.diagnostic_test
[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging
Experimental validation
Diabetic Macular Edema
[ SDV.MHEP.OS ] Life Sciences [q-bio]/Human health and pathology/Sensory Organs
Optical Coherence Tomography
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Research Article
Article Subject
Local binary patterns
03 medical and health sciences
Speckle pattern
Optical coherence tomography
[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathology
Medical imaging
medicine
DME
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Coherence (signal processing)
Texture
[SDV.MHEP.OS]Life Sciences [q-bio]/Human health and pathology/Sensory Organs
Retinopathy
[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
business.industry
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Pattern recognition
eye diseases
Ophthalmology
OCT
lcsh:RE1-994
030221 ophthalmology & optometry
Images
Artificial intelligence
business
030217 neurology & neurosurgery
[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Zdroj: American Journal of Ophthalmology
American Journal of Ophthalmology, Elsevier Masson, 2016, 2016, pp.1-14. 〈https://www.hindawi.com/journals/joph/2016/3298606/〉. 〈10.1155/2016/3298606〉
American Journal of Ophthalmology, Elsevier Masson, 2016, 2016, pp.1-14. ⟨10.1155/2016/3298606⟩
Journal of Ophthalmology
Journal of Ophthalmology, Hindawi Publishing Corporation, 2016, 2016
Journal of Ophthalmology, Vol 2016 (2016)
ISSN: 0002-9394
2090-004X
2090-0058
DOI: 10.1155/2016/3298606〉
Popis: International audience; This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with Diabetic Macular Edema (DME) versus normal subjects. Optical Coherence Tomography (OCT) has been a valuable diagnostic tool for DME, which is among the most common causes of irreversible vision loss in individuals with diabetes. Here, a classification framework with five distinctive steps is proposed and we present an extensive study of each step. Our method considers combination of various pre-processings in conjunction with Local Binary Patterns (LBP) features and different mapping strategies. Using linear and non-linear classifiers, we tested the developed framework on a balanced cohort of 32 patients. Experimental results show that the proposed method outperforms the previous studies by achieving a Sensitivity (SE) and Specificity (SP) of 81.2% and 93.7%, respectively. Our study concludes that the 3D features and high-level representation of 2D features using patches achieve the best results. However, the effects of pre-processing is inconsistent with respect to different classifiers and feature configurations.
Databáze: OpenAIRE
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