Spine Disease Detection in Spinal X-Ray Images using Machine Learning
Millions of individuals globally experience spinal ailments. This stresses the importance of swift detection for achieving better treatment results. Traditional diagnosis techniques can be lengthy. They might lack precision. So here the aim is to design a powerful yet budget-friendly system that employs a deep neural network which has been trained on a vast X-ray image database. The system aims at carrying out X-ray scans of spinal vertebrae with improved accuracy. The method proposed utilizes a lite deep neural network to gather information. This is done from numerous levels to aid. In the detection of spinal health conditions, the autonomous system for finding spine illnesses consist crucial elements. These include photo filtering tools attribute excavation methods and efficient classification algorithms. Moreover, Clinical information and patient past records are added to the analyses. This augments the diagnostic precision and dependability of the system.
Authors
- Nandini Sharma (ORCID: https://orcid.org/0000-0001-7885-4901)
- Swati Vishnoi (ORCID: https://orcid.org/0000-0001-6846-108X)
- Medha Khenwar (ORCID: https://orcid.org/0000-0002-0071-1078)
- Dushyant Singh Chauhan (ORCID: https://orcid.org/0000-0002-0380-7518)
- Ankur Sisodia
- P.K. Gupta (ORCID: https://orcid.org/0000-0002-6057-7616)
Institutions
- Banasthali University (IN)
- The Sanskrit College and University (IN)
- CT Group Of Institutions (IN)
- GLA University (IN)
Publication Details
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1109/smart63812.2024.10882486
- Citations
- 3
- Primary Topic
- Medical Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.55