E-ISSN 0976-2833 | ISSN 0975-3583
 

Research Article 


Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri, Tirumalasetty Satya Prabhasa, Sai Ram Maganti , Ganesh Reddy Chanda.

Abstract
Lower back pain is mainly caused by some complications present in the lumbar spine. In general, human beings face a lot of problems with lower back pain and very few people figure out the exact cause, and most of them unable to find the exact cause behind the pain. As we know that the diagnosis of a medical record is very complex and plays a crucial role to the medical persons in order to treat the patients who suffer with low back pain. In general, the medical practitioner tries to study the abnormality present in the medical records like MRI or Scan images in a manual manner under direct eye contact, which is a very complicated task to figure out the minute abnormalities which is present inside the report. This motivated me to design this proposed application using machine learning (ML) models in the medical field for disease prediction and to guide the medical experts about the patientís current situation. In this present work, we try to identify the most important physical parameters which are required to figure out the spinal abnormalities which are collected physically from spine patients. Here we propose a novel method to predict and trace the lumbar spinal stenosis through semantic segmentation and delineation of magnetic resonance imaging (MRI) scans of the lumbar spine. By conducting various experiments on the spine dataset which contain nearly 575 MRI studies of patients who are having symptomatic back pain. Our theoretical and experimental results clearly state that proposed method produces a very good performance as compared with primitive region-based metrics.

Key words: Magnetic Resonance Imaging (MRI), Machine Learning, Lumbar Spinal Stenosis Detection, Semantic Segmentation, Clinicians.


 
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How to Cite this Article
Pubmed Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda. Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique. J Cardiovasc. Dis. Res.. 2021; 12(4): 702-713. doi: 10.31838/jcdr.2021.12.04.80


Web Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda. Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique. http://www.jcdronline.org/?mno=100270 [Access: July 26, 2021]. doi: 10.31838/jcdr.2021.12.04.80


AMA (American Medical Association) Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda. Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique. J Cardiovasc. Dis. Res.. 2021; 12(4): 702-713. doi: 10.31838/jcdr.2021.12.04.80



Vancouver/ICMJE Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda. Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique. J Cardiovasc. Dis. Res.. (2021), [cited July 26, 2021]; 12(4): 702-713. doi: 10.31838/jcdr.2021.12.04.80



Harvard Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda (2021) Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique. J Cardiovasc. Dis. Res., 12 (4), 702-713. doi: 10.31838/jcdr.2021.12.04.80



Turabian Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda. 2021. Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique. Journal of Cardiovascular Disease Research, 12 (4), 702-713. doi: 10.31838/jcdr.2021.12.04.80



Chicago Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda. "Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique." Journal of Cardiovascular Disease Research 12 (2021), 702-713. doi: 10.31838/jcdr.2021.12.04.80



MLA (The Modern Language Association) Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda. "Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique." Journal of Cardiovascular Disease Research 12.4 (2021), 702-713. Print. doi: 10.31838/jcdr.2021.12.04.80



APA (American Psychological Association) Style

Gadu Srinivasa Rao , Rushil Desetty , Edulakanti Richa Reddy , Yeshwanth thalluri , Tirumalasetty Satya Prabhasa , Sai Ram Maganti , Ganesh Reddy Chanda (2021) Detect and Analyze the Performance of Lumbar Spinal Stenosis Detection from MRI Images by Using Semantic Segmentation Technique. Journal of Cardiovascular Disease Research, 12 (4), 702-713. doi: 10.31838/jcdr.2021.12.04.80





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