Macular OCT Classification Using a Multi-Scale Convolutional Neural Network Ensemble

• Published in: IEEE transactions on medical imaging Vol. 37; no. 4; pp. 1024 - 1034
• Main Authors: Rasti, Reza, Rabbani, Hossein, Mehridehnavi, Alireza, Hajizadeh, Fedra
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Age; Algorithms; Artificial neural networks; CAD system; Classification; Databases, Factual; Datasets; Diabetes; Diabetes mellitus; Edema; Electronic devices; Eye diseases; Feature extraction; Ground truth; Humans; Image analysis; Image Interpretation, Computer-Assisted - methods; Image processing; Imaging; Macula Lutea - diagnostic imaging; Macular degeneration; Macular Degeneration - diagnostic imaging; macular pathology; Medical imaging; Medical treatment; Modular structures; Multi-scale Convolutional Mixture of Experts (MCME); Neural networks; Neural Networks (Computer); Noise reduction; Optical Coherence Tomography; Optical Coherence Tomography (OCT); Pathology; Probabilistic models; Rangefinding; Retina; Solid modeling; Tomography, Optical Coherence - methods

Computer-aided diagnosis (CAD) of retinal pathologies is a current active area in medical image analysis. Due to the increasing use of retinal optical coherence tomography (OCT) imaging technique, a CAD system in retinal OCT is essential to assist ophthalmologist in the early detection of ocular dis...