Image Denoising Techniques on Medical and Microscopic Images
G Krishna Chaitanya
, K Bilva Sai , M Sumit Reddy , V Durgesh , Deepthi Murthy
Denoising is the first step any image processing engineer working with MRI images performs. Nowadays Medical imaging in technique Magnetic Resonance Imaging (MRI) plays an important role in medical setting to form high standard images of the human brain. MRI is commonly used once treating brain, prostate cancers, ankle and foot.While deep learning approaches for denoising sound promising, it still remains an actively researched application for MRI images. Until someone publishes a deep learning trained model that works on all MRI images we have resort to traditional methods for denoising. In fact, traditional methods may turn out to be far more efficient and accurate compared with deep learning. This paper covers a few ways to denoise MRI images using heavily researched and validated approaches such as Gaussian algorithms. Smoothing, bilateral filtering, anisotropic diffusion, non-local means, and Block-matching and 3D filtering (BM3D) algorithms. Microscopy is an essential part of a biologist’s daily work, allowing assaying of many parameters such as sub- cellular localisation of proteins, changes in cytoskeletal dynamics. A fundamental challenge that is faced even in microscopy is the presence of noise. To denoise microscope images we are using same algorithms as mentioned in MRI images.
"Image Denoising Techniques on Medical and Microscopic Images", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.c84-c90, March-2023, Available :https://ijnrd.org/papers/IJNRD2303214.pdf
Volume 8
Issue 3,
March-2023
Pages : c84-c90
Paper Reg. ID: IJNRD_188955
Published Paper Id: IJNRD2303214
Downloads: 000118987
Research Area: Engineering
Country: BANGALURU, Karnataka, India
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
