Automatic recognition of retinal diseases using mathematical models of image processing, based on multilayer-dictionary learning

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MONTAZERI AZADEH; Shamsi Mahboubeh; DIANAT ROUHOLLAH

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Journal: Technology of Education Journal Year:2019 | Volume:13 | Issue:3 Page(s): 371-386

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Information Journal Paper

Title

Automatic recognition of retinal diseases using mathematical models of image processing, based on multilayer-dictionary learning

Author(s)

MONTAZERI AZADEH | Shamsi Mahboubeh | DIANAT ROUHOLLAH | Issue Writer Certificate

Keywords

Multi-layer Dictionary LearningQ1

Sparse RepresentationQ1

K-SVD AlgorithmQ1

Optical CoherenceQ1

TomographyQ2

ClassificationQ2

Abstract

The purpose of this study is to improve the Classification of new methods using a multi-layered model to address retinal diseases diagnosis. This paper presents a Multi-layer Dictionary Learning method for Classification tasks. Our multi-layer framework uses a label consistent in K-SVD Algorithm to learn a discriminative dictionary for sparse coding in order to learn better features in retinal Optical Coherence Tomography images. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discrimination in sparse codes during dictionary learning process. In fact, it relies on a succession of sparse coding and pooling steps in order to find an effective representation of data for Classification. Moreover, we apply Duke dataset for validating our algorithm: Duke spectral domain OCT (SD-OCT) dataset, consisting of volumetric scans acquired from 45 subjects 15 normal subjects, 15 AMD patients, and 15 DME patients. Our classifier leads to a correct Classification rate of 95. 85% and 100. 00% for normal and abnormal (DME and AMD). Experimental results demonstrate that our algorithm outperforms compared to many recent proposed supervised dictionary learning and Sparse Representation techniques.

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APA: Copy

MONTAZERI, AZADEH, Shamsi, Mahboubeh, & DIANAT, ROUHOLLAH. (2019). Automatic recognition of retinal diseases using mathematical models of image processing, based on multilayer-dictionary learning. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), 13(3 ), 371-386. SID. https://sid.ir/paper/155367/en

Vancouver: Copy

MONTAZERI AZADEH, Shamsi Mahboubeh, DIANAT ROUHOLLAH. Automatic recognition of retinal diseases using mathematical models of image processing, based on multilayer-dictionary learning. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION)[Internet]. 2019;13(3 ):371-386. Available from: https://sid.ir/paper/155367/en

IEEE: Copy

AZADEH MONTAZERI, Mahboubeh Shamsi, and ROUHOLLAH DIANAT, “Automatic recognition of retinal diseases using mathematical models of image processing, based on multilayer-dictionary learning,” JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), vol. 13, no. 3 , pp. 371–386, 2019, [Online]. Available: https://sid.ir/paper/155367/en

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