Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL

Authors

  • Rayudu Srinivas

Keywords:

IVD, VESTAL, statistics, vertebrae, intervertebral, disc, classification

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.

How to Cite

Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL. (2015). Global Journal of Medical Research, 15(D1), 27-34. https://medicalresearchjournal.org/index.php/GJMR/article/view/888

References

Immanuel Sebastine, David Williams (2004) Current Developments in Tissue Engineering of Nucleus Pulposus for the Treatment of Intervertebral Disc Degeneration.

B Bechara, B Bowman, S Leckie, G Sowa, J Kang A Novel Computerized Algorithm to Quantify MRI Signal Changes in Invertebral Disc Degeneration. 1350.

Jennifer Vernengo, Anthony Lowman (2007) Injectable bioadhesive hydrogels for nucleus pulposus replacement and repair of the damaged intervertebral disc.

R Gunzburg, R Parkinson, R Moore, F Cantraine, W Hutton, B Vernon Roberts, R Fraser, ; Hothorn, B Lausen (1992) Bagging tree classifiers for laser scanning images: a data-and simulation based strategy. 27(1), 65-79.

A Sharkey, N Sharkey, S Cross (1988) Adapting an ensemble approach for the diagnosis of breast cancer. 281-286.

Z.-H Zhou, Y Jiang, Y.-B Yang, S.-F Chen (2002) Lung cancer cell identification based on artificial neural network ensembles. 24(1), 25-36.

R Srinivas, K Ramana (2015) A fully automated new flanged VESTAL to Label cervical vertebrae and inter vertebral discs" 3 rd International conferece on Recent trends in computing accepted.

P Violas, I Estlvalezes, J Bnot, P Sales De Gauzy, Swider (2007) Objective quantification of Intervertebral disc volume properties Using MRI in idiopathic scoliosis surgery. 25(3), 386-391.

R Niemeläinen, T Videman, S Dhillon, M Battié (2008) Quantitative measurement of intervertebral disc signal using MRI. 63(3), 252-255.

Tobias Klinder, Jörn Ostermann, Matthias Ehm, Astrid Franz, Reinhard Kneser, Cristian Lorenz (2009) Automated model-based vertebra detection, identification, and segmentation in CT images. 13(3), 471-482.

Samuel Kadoury, Hubert Labelle, Nikos Paragios (2013) Spine Segmentation in Medical Images Using Manifold Embeddings and Higher-Order MRFs. 32(7), 1227-1238.

Yiebin Kim, Dongsung Kim (2009) A fully automatic vertebra segmentation method using 3D deformable fences. 33, 343-352.

B Kelm, Michael Wels, S Zhou, Sascha Seifert, Michael Suehling, Yefeng Zheng, Dorin Comaniciu (2013) Spine detection in CT and MR using iterated marginal space learning. 17, 1283-1292.

W Max, Kengyeow Law, Andrew Tay, Gregory Leung, Shuo Garvin, Li (2013) Intervertebral disc segmentation in MR images using anisotropic oriented flux. 17, 43-61.

Claudia Chevrefils, Farida Cheriet, Carl Aubin, Guy Grimard (2009) Texture Analysis for Automatic Segmentation of Intervertebral Disks of Scoliotic Spines From MR Images. 13(4).

Y Ünal, H Koçer, H Akkurt (2011) Automatic Diagnosis of Intervertebral Degenerative Disk Disease Using Artificial neural network. 16-18.

Sofia Michopoulou, Lena Costaridou, Elias Panagiotopoulos, Robert Speller, George Panayiotakis, Andrew Todd-Pokropek (2009) Atlas-Based Segmentation of Degenerated Lumbar Intervertebral Discs From MR Images of the Spine. 56(9), 2225-2231.

' Raja, Jason Alomaria, Vipin Corsoa, Gurmeet Chaudharya, Dhillon (2011) Automatic Diagnosis of Lumbar Disc Herniation with Shape and Appearance Features from MRI. 30(1).

Shijie Hao, Jianguo Jiang, Yanrong Guo, Shu Zhan (2011) Intervertebral Disc Shape Analysis with Geodesic Metric in Shape Space.

Nuket Gocmen-Mas, Hamit Karabekir, Tolga Ertekin, Mete Edizer, Yazici Canan, Izzet Duyar (2010) Evaluation of Lumbar Vertebral Body and Disc: A Stereological Morphometric Study. 28(3), 841-847.

Ming-Chi Wu, Cheng-An Fang (2012) Degenerative disc segmentation and diagnosis technology using important features from MRI of spine in images. 190-193.

Neil Roberts, Christophe Gratin, Graham Whitehouse (1997) MRI analysis of lumbar intervertebral disc height in young and older populations. 7(5), 880-886.

Claudia Chevrefils, Farida Chériet, Guy Grimard, Carl-Eric Aubin (2007) Watershed Segmentation of Intervertebral Disk and Spinal Canal from MRI Images. 4633, 1017-1027.

R Shil, D Sun, Z Qiu, K Weiss (2007) An efficient method for segmentation of MRI spine images. 713-717.

I Wachter, S Seifert, R Dillmann (2005) Automatic segmentation of cervical soft tissue from MR Images. 81-88.

Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL

Published

2015-05-28

How to Cite

Classification of Intervertebral Disc Degeneration (IVDD) using VESTAL. (2015). Global Journal of Medical Research, 15(D1), 27-34. https://medicalresearchjournal.org/index.php/GJMR/article/view/888