Manuscript Number : IJSRST24113258

Denoising and Segmentation of Medical Images Using N2S-U-Net

Authors(2) :-G Ashwini, Dr. T. Ramashri

Medical image processing faces significant chal- lenges, particularly in the denoising and segmentation of images where noise can severely degrade quality and affect diagnostic accuracy. This study presents a novel hybrid approach combining N2S-U-Net for image denoising with an enhanced U-Net architec- ture for segmentation. The N2S-U-Net model effectively denoises medical images without the need for paired clean images, en- hancing the subsequent segmentation process. Our approach has been evaluated on multiple imaging modalities, including chest X- rays (CXR), computed tomography (CT), and microscopy images. Results demonstrate substantial improvements in segmentation performance compared to conventional methods, underscoring the potential of this integrated approach to enhance diagnostic accuracy across diverse medical imaging modalities.

Authors and Affiliations

G Ashwini
Department of Electronics and Communication Engineering SV University, Tirupati, India
Dr. T. Ramashri
Department of Electronics and Communication Engineering SV University, Tirupati, India

Medical Imaging; Image Denoising; N2S-U-Net; Image Segmentation; Deep Learning

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Publication Details

Published in : Volume 10 | Issue 6 | November-December 2023
Date of Publication : 2023-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 586-594
Manuscript Number : IJSRST24113258
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

G Ashwini, Dr. T. Ramashri, " Denoising and Segmentation of Medical Images Using N2S-U-Net", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 10, Issue 6, pp.586-594, November-December-2023.
Journal URL : https://ijsrst.com/IJSRST24113258
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