NDLI: Sparse representation based computed tomography images reconstruction by coupled dictionary learning algorithm

Content Provider	IET Digital Library
Author	Deeba, Farah Kun, She Dharejo, Fayaz Ali Zhou, Yuanchun
Abstract	It is very interesting to reconstruct high-resolution computed tomography (CT) medical images that are very useful for clinicians to analyse the diseases. This study proposes an improved super-resolution method for CT medical images in the sparse representation domain with dictionary learning. The sparse coupled K-singular value decomposition (KSVD) algorithm is employed for dictionary learning purposes. Images are divided into two sets of low resolution (LR) and high resolution (HR), to improve the quality of low-resolution images, the authors prepare dictionaries over LR and HR image patches using the KSVD algorithm. The main idea behind the proposed method is that sparse coupled dictionaries learn about each patch and establish the relationship between sparse coefficients of LR and HR image patches to recover the HR image patch for LR image. The proposed method is compared to conventional algorithms in terms of mean peak signal-to-noise ratio and structural similarity index measurements by using three different data set images, including CT chest, CT dental and CT brain images. The authors also analysed the proposed improved method for different dictionary sizes and patch size to obtain a similar high-resolution image. These parameters play an essential role in the reconstruction of the HR images.
Starting Page	2365
Ending Page	2375
Page Count	11
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 11, Sep (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.1312
Journal	IET Image Processing
Publisher Date	2020-04-02
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Biology And Medical Computing Biomedical Imaging/measurement Brain Computed Tomography Image Reconstruction Computer Vision And Image Processing Technique Computerised Tomography Conventional Algorithm Coupled Dictionary CT Medical Image Dictionaries Dictionary Learning Purposes Different Dictionary Sizes Diseases Graph Theory High-resolution Computed Tomography Medical Image High-resolution Image High-resolution Reconstruction-based Method HR Image HR Image Patch Image Analysis Image Denoising Image Patches Image Processing Application Image Reconstruction Image Representation Image Resolution K-singular Value Decomposition Algorithm Knowledge Engineering Technique KSVD Algorithm Learning in AI Low-resolution Image LR Image Medical Image Medical Image Processing Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Radiography And Computed Tomography Set Theory Singular Value Decomposition Sparse Coefficient Sparse Coupled Dictionaries Sparse Representation Domain Super-resolution Method X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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