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Low MSE Based Brain Region Segmentation With CNN Using WLS Filter
Subject area: Science,Engineering and Technology · Area of research: Engineering
Abstract
Brain region segmentation in MRI based images is a crucial step for empirical analysis of the main anatomical structures of the brain in large-scale studies. Brain region segmentation is of paramount importance because it helps experts to focus on specific regions of the brain to study them. However, segmentation of the brain region can be a difficult task due to high similarities and correlations of intensity among different regions of the brain image. Therefore in order to mitigate these challenging tasks, there is a need for objective diagnosis and efficient processing of the MRI based brain images. This paper proposes a method in which the brain region is segmented using deep learning based semantic segmentation (CNN) which is combined with WLS filter for better accuracy and low MSE (Mean Square Error).
Keywords
Brain region segmentation, Deep learning, CNN, Image processing, WLS filter, MSE
References
[1] Dr. D. Selvathi, T.Vanmathi, “Brain Region Segmentation using Convolutional Neural Network” 978-1-5386-3695-4$31.00_c 2018 IEEE
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[3] Alpana Jijja, Dr. Dinesh Rai, “Efficient MRI Segmentation and Detection of Brain Tumor using Convolutional Neural Network” (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 10, No. 4, 2019
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[5] Hapsari Peni Agustin Tjahyaningtijas, “Brain Tumor Image Segmentation in MRI Image” Materials Science and Engineering 336 (2018) 012012 doi:10.1088/1757-899X/336/1/012012
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[8] Z. Zhang and C. Jung, "Structure tensor-based WLS filter for adaptive smoothing," 2016 Visual Communications and Image Processing (VCIP), Chengdu, China, 2016, pp. 1-4.
How to cite this paper
@article{1702807,
author = {Neetu Khichar, Preeti Vyas},
title = {Low MSE Based Brain Region Segmentation With CNN Using WLS Filter},
journal = {Iconic Research And Engineering Journals},
year = {2021},
volume = {5},
number = {1},
pages = {28-33},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1702807.pdf},
abstract = {Brain region segmentation in MRI based images is a crucial step for empirical analysis of the main anatomical structures of the brain in large-scale studies. Brain region segmentation is of paramount importance because it helps experts to focus on specific regions of the brain to study them. However, segmentation of the brain region can be a difficult task due to high similarities and correlations of intensity among different regions of the brain image. Therefore in order to mitigate these challenging tasks, there is a need for objective diagnosis and efficient processing of the MRI based brain images. This paper proposes a method in which the brain region is segmented using deep learning based semantic segmentation (CNN) which is combined with WLS filter for better accuracy and low MSE (Mean Square Error).},
keywords = {Brain region segmentation, Deep learning, CNN, Image processing, WLS filter, MSE},
month = {July},
}