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  Published Paper Details:

  Paper Title

INVESTIGATION OF AN EARLY IDENTIFICATION & MEASUREMENT OF OSTEOARTHRITIS SERIOUSNESS IN KNEE USING MACHINE LEARNING

  Authors

  T.P Ann Thabitha,  Megha Seth,  Suyash Agrawal,  Rakhi Seth

  Keywords

MRI, Osteoarthritis, OA detection, Classification, Machine Learning, Deep learning.

  Abstract


The major cause of frailty in older and overweight people is Osteoarthritis. It is a joint illness that generally influences the ligament that could be principally affects the cartilage. Cartilage is a smooth elastic tissue which makes the bones move easily, stabilizes the joint and prevents them from abrading one another. The protective cartilage in Osteoarthritis is ruptured and makes the bones rub one another, inflicting joint stiffness and excessive pain. The current system for the assessment of Osteoarthritis incorporates clinical examination and restorative imaging methods. In this project, by utilizing profound features and medical images we need to recognize and classify OA affected in knee. This can impact on the detection and classification of target area in images and cause of it the irrelevant features could be selected from the medical images. This article will moreover center on dealing the colossal quantity of image information by using high speed computing. This paper also discovers the Magnetic Resonance Imaging (MRI) techniques for detection and classification of Osteoarthritis in descriptive and comparative manner.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2008347

  Paper ID - 198121

  Page Number(s) - 3037-3041

  Pubished in - Volume 8 | Issue 8 | August 2020

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  T.P Ann Thabitha,  Megha Seth,  Suyash Agrawal,  Rakhi Seth,   "INVESTIGATION OF AN EARLY IDENTIFICATION & MEASUREMENT OF OSTEOARTHRITIS SERIOUSNESS IN KNEE USING MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 8, pp.3037-3041, August 2020, Available at :http://www.ijcrt.org/papers/IJCRT2008347.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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