8 February 2017 High resolution OCT image generation using super resolution via sparse representation
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Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 1022512 (2017) https://doi.org/10.1117/12.2266337
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan
Abstract
In this paper we propose a technique for obtaining a high resolution (HR) image from a single low resolution (LR) image -using joint learning dictionary - on the basis of image statistic research. It suggests that with an appropriate choice of an over-complete dictionary, image patches can be well represented as a sparse linear combination. Medical imaging for clinical analysis and medical intervention is being used for creating visual representations of the interior of a body, as well as visual representation of the function of some organs or tissues (physiology). A number of medical imaging techniques are in use like MRI, CT scan, X-rays and Optical Coherence Tomography (OCT). OCT is one of the new technologies in medical imaging and one of its uses is in ophthalmology where it is being used for analysis of the choroidal thickness in the eyes in healthy and disease states such as age-related macular degeneration, central serous chorioretinopathy, diabetic retinopathy and inherited retinal dystrophies. We have proposed a technique for enhancing the OCT images which can be used for clearly identifying and analyzing the particular diseases. Our method uses dictionary learning technique for generating a high resolution image from a single input LR image. We train two joint dictionaries, one with OCT images and the second with multiple different natural images, and compare the results with previous SR technique. Proposed method for both dictionaries produces HR images which are comparatively superior in quality with the other proposed method of SR. Proposed technique is very effective for noisy OCT images and produces up-sampled and enhanced OCT images.
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Muhammad Asif, Muhammad Asif, Muhammad Usman Akram, Muhammad Usman Akram, Taimur Hassan, Taimur Hassan, Arslan Shaukat, Arslan Shaukat, Razi Waqar, Razi Waqar, } "High resolution OCT image generation using super resolution via sparse representation", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 1022512 (8 February 2017); doi: 10.1117/12.2266337; https://doi.org/10.1117/12.2266337
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