Efficient MRI image enhancement by improved denoising techniques for better skull stripping using attention module-based convolution neural network-Reference-Cited by-同舟云学术

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Efficient MRI image enhancement by improved denoising techniques for better skull stripping using attention module-based convolution neural network

Published:2024-08-06 Issue:1 Volume:12 Page:
ISSN:2168-1163
Container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Author:

Jeme V Jesline¹,Jerome S Albert²

Affiliation:

1. Research Scholar, Department of Electronics and Communication Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Thuckalay, TamilNadu, India

2. Department of Biomedical, Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Thuckalay, TamilNadu, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/21681163.2024.2309874

Reference49 articles.

1. DeepMNF: Deep Multimodal Neuroimaging Framework for Diagnosing Autism Spectrum Disorder;Abbas S;Artif Intell Med,2023

2. Perceptually Motivated Generative Model for Magnetic Resonance Image Denoising;Aetesam H;J Digit Imaging,2023

3. Denoising of nifti (mri) images with a regularized neighborhood pixel similarity wavelet algorithm;Akindele RG;Sensors,2023

4. Benson CC, and Lajish VL. 2014. Morphology based enhancement and skull stripping of MRI brain images. 2014 International Conference on intelligent computing applications; Coimbatore, India; p. 254–257.

5. NLM based magnetic resonance image denoising–A review;Bhujle HV;Biomed Signal Process Control,2019

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