Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL

Rayudu Srinivas

Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL

Rayudu Srinivas * § B.Tech.,M.Tech., (Ph.D)

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Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL

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Abstract

Spine is the most essential part of human body. Vertebrae and intervertebral discs are important parts of Spine. The Inter vertebral disc (IVD) is a complex and load bearing structure. IVD undergoes a process of change with age and leads to failures. This paper presents a novel model to detect IVD failures using Magnetic Resonance (MR) images. The proposed method makes use of Vertebrae Statistics description Algorithm (VESTAL) to create a template by extracting features from several MR images contains healthy IVDs. The proposed method measures IVD and vertebrae features like intensity, anterior width, posterior width and center length of IVD. A template is created by VESTAL algorithm by extracting feature from 220 healthy IVD images in this work. The proposed method is implemented on 45 case studies where IVD failure have taken place. Proposed method detected the failure region and classified the IVDwith 94% accuracy.

References

25 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Rayudu Srinivas. 2015. "Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL". Global Journal of Medical Research - D: Radiology, Diagnostic GJMR-D Volume 15 (GJMR Volume 15 Issue D1).

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GJMR Volume 15 Issue D1

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Journal Specifications

Crossref Journal DOI 10.17406/gjmr

Print ISSN 0975-5888

e-ISSN 2249-4618

Keywords

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Classification

GJMR-D Classification NLMC Code: WE 740

Submission ReceivedApril 8, 2015
Peer Review Double Blind
Handling Editor
Accepted May 2, 2015
Published May 15, 2015

Version of record

v1.2

Issue date

May 28, 2015

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Medical Research

Authors: Rayudu Srinivas, K V Ramana (PhD/Dr. count: 0)

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