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  1. Home
  2. Volume 7, Issue 11
  3. Author

Online ISSN: 2515-8260

Volume7, Issue11

CLASSIFICATION OF DEFECTED SPINE AND SEGMENTATION USING DEEP LEARNING

    Mrs. G. Valarmathi, Dr. B. Ashraf Ahmed, S.Padmapriya, M. Shafana Aasmi, M. N. Varshini

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 11, Pages 1546-1554

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Abstract

This paper presents an efficient method to delineate the degenerated portion of the spinal cord from magnetic resonance images (MRI) of the patients. One of the major issue in human body is back pain. To diagnose the problems in lumbar region of spine we use deep learning neural networks using Convolutional Neural Networks(CNN) algorithm which can take in an input image, assign importance to various aspects/objects in the image and be able to differentiate one from the other .By using this CNN algorithm we get a meticulous result.. Spine is the principal transmission pathway for neural signals between the brain and the rest of the body. The primary purpose of this paper is to compare various methods used for segmentation of spine. Matlab has been used to perform spine segmentation and classification.Our approach produces better segmentation results than other existing methods.
 
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(2020). CLASSIFICATION OF DEFECTED SPINE AND SEGMENTATION USING DEEP LEARNING. European Journal of Molecular & Clinical Medicine, 7(11), 1546-1554.
Mrs. G. Valarmathi, Dr. B. Ashraf Ahmed, S.Padmapriya, M. Shafana Aasmi, M. N. Varshini. "CLASSIFICATION OF DEFECTED SPINE AND SEGMENTATION USING DEEP LEARNING". European Journal of Molecular & Clinical Medicine, 7, 11, 2020, 1546-1554.
(2020). 'CLASSIFICATION OF DEFECTED SPINE AND SEGMENTATION USING DEEP LEARNING', European Journal of Molecular & Clinical Medicine, 7(11), pp. 1546-1554.
CLASSIFICATION OF DEFECTED SPINE AND SEGMENTATION USING DEEP LEARNING. European Journal of Molecular & Clinical Medicine, 2020; 7(11): 1546-1554.
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