Biomaterial Database

Macular OCT Classification Using a Multi-Scale Convolutional Neural Network Ensemble. 2018

Reza Rasti, and Hossein Rabbani, and Alireza Mehridehnavi, and Fedra Hajizadeh

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 diseases and treatment monitoring. This paper presents a novel CAD system based on a multi-scale convolutional mixture of expert (MCME) ensemble model to identify normal retina, and two common types of macular pathologies, namely, dry age-related macular degeneration, and diabetic macular edema. The proposed MCME modular model is a data-driven neural structure, which employs a new cost function for discriminative and fast learning of image features by applying convolutional neural networks on multiple-scale sub-images. MCME maximizes the likelihood function of the training data set and ground truth by considering a mixture model, which tries also to model the joint interaction between individual experts by using a correlated multivariate component for each expert module instead of only modeling the marginal distributions by independent Gaussian components. Two different macular OCT data sets from Heidelberg devices were considered for the evaluation of the method, i.e., a local data set of OCT images of 148 subjects and a public data set of 45 OCT acquisitions. For comparison purpose, we performed a wide range of classification measures to compare the results with the best configurations of the MCME method. With the MCME model of four scale-dependent experts, the precision rate of 98.86%, and the area under the receiver operating characteristic curve (AUC) of 0.9985 were obtained on average.

UI	MeSH Term	Description	Entries
D007090	Image Interpretation, Computer-Assisted	Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease.	Image Interpretation, Computer Assisted,Computer-Assisted Image Interpretation,Computer-Assisted Image Interpretations,Image Interpretations, Computer-Assisted,Interpretation, Computer-Assisted Image,Interpretations, Computer-Assisted Image
D008266	Macula Lutea	An oval area in the retina, 3 to 5 mm in diameter, usually located temporal to the posterior pole of the eye and slightly below the level of the optic disk. It is characterized by the presence of a yellow pigment diffusely permeating the inner layers, contains the fovea centralis in its center, and provides the best phototropic visual acuity. It is devoid of retinal blood vessels, except in its periphery, and receives nourishment from the choriocapillaris of the choroid. (From Cline et al., Dictionary of Visual Science, 4th ed)	Lutea, Macula,Luteas, Macula,Macula Luteas
D008268	Macular Degeneration	Degenerative changes in the RETINA usually of older adults which results in a loss of vision in the center of the visual field (the MACULA LUTEA) because of damage to the retina. It occurs in dry and wet forms.	Maculopathy,Maculopathy, Age-Related,Age-Related Macular Degeneration,Age-Related Maculopathies,Age-Related Maculopathy,Macular Degeneration, Age-Related,Macular Dystrophy,Maculopathies, Age-Related,Age Related Macular Degeneration,Age Related Maculopathies,Age Related Maculopathy,Age-Related Macular Degenerations,Degeneration, Macular,Dystrophy, Macular,Macular Degeneration, Age Related,Macular Degenerations,Macular Dystrophies,Maculopathies,Maculopathy, Age Related
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000465	Algorithms	A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.	Algorithm
D016208	Databases, Factual	Extensive collections, reputedly complete, of facts and data garnered from material of a specialized subject area and made available for analysis and application. The collection can be automated by various contemporary methods for retrieval. The concept should be differentiated from DATABASES, BIBLIOGRAPHIC which is restricted to collections of bibliographic references.	Databanks, Factual,Data Banks, Factual,Data Bases, Factual,Data Bank, Factual,Data Base, Factual,Databank, Factual,Database, Factual,Factual Data Bank,Factual Data Banks,Factual Data Base,Factual Data Bases,Factual Databank,Factual Databanks,Factual Database,Factual Databases
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D041623	Tomography, Optical Coherence	An imaging method using LASERS that is used for mapping subsurface structure. When a reflective site in the sample is at the same optical path length (coherence) as the reference mirror, the detector observes interference fringes.	OCT Tomography,Optical Coherence Tomography,Coherence Tomography, Optical,Tomography, OCT