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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 176 - Issue 38 |
| Published: Jul 2020 |
| Authors: Shaheera Rashwan, Ashraf Khalil |
10.5120/ijca2020920474
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Shaheera Rashwan, Ashraf Khalil . Two Dimensional Gel Electrophoresis Image Inpainting for Improving Protein Spot Detection. International Journal of Computer Applications. 176, 38 (Jul 2020), 38-41. DOI=10.5120/ijca2020920474
@article{ 10.5120/ijca2020920474,
author = { Shaheera Rashwan,Ashraf Khalil },
title = { Two Dimensional Gel Electrophoresis Image Inpainting for Improving Protein Spot Detection },
journal = { International Journal of Computer Applications },
year = { 2020 },
volume = { 176 },
number = { 38 },
pages = { 38-41 },
doi = { 10.5120/ijca2020920474 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2020
%A Shaheera Rashwan
%A Ashraf Khalil
%T Two Dimensional Gel Electrophoresis Image Inpainting for Improving Protein Spot Detection%T
%J International Journal of Computer Applications
%V 176
%N 38
%P 38-41
%R 10.5120/ijca2020920474
%I Foundation of Computer Science (FCS), NY, USA
Many specialized software programs are available for processing two dimensional gel electrophoresis (2-DGE) images. However, the anomalies existing in these images make the achievement of a reliable system for 2-DGE image analysis still difficult to reach. In this paper, we propose a new preprocessing technique applied to 2-DGE images. The new technique is based on image inpainting using Mumford Shah Euler Lagrange to discard anomalies such as vertical and horizontal streaking from these images. We also present a comparison of the analysis of 2-DGE images inpainted by the proposed technique and non-inpainted images using the known commercial software Delta2D. We compute the F-measure in both cases for three different 2-DGE images. The degree of improvement in F-measure reaches 18.5% in first image and 5.9% in second image and 3.8% in third image. Our new 2D Gel image preprocessing method based on Mumford Shah inpainting shows a significant improvement when comparing analysis of inpainted images with non-inpainted images.