Total views : 217

Lumbar Spine Classification using Pyramidal Histogram of Oriented Gradients

Affiliations

  • Department of CSE, SSN College of Engineering, Chennai - 603110, Tamil Nadu, India

Abstract


Objective: To diagnose any injury in the lumbar region of human spine, the classification of each vertebra and Intervertebral Disc (IVD) is the vital task. Methods: The classification of the lumbar structure is done using Pyramidal Histogram of Gradients (PHOG). The PHOG technique is applied on the MR Image to select the basic intensity level features. These features are trained with Support Vector Machine (SVM). After building a model with SVM classification algorithm, classify the MR Images for discs and vertebrae separately. Findings: The accuracy is calculated to verify the performance of this work. This classification procedure is performed on a lumbar MR image dataset which contains 960 IVDs and 800 vertebrae with T1 and T2 weighted for 80 subjects.

Keywords

Classification, Intervertebral Discs, Lumbar spine, Pyramidal Histogram of Oriented Gradients (PHOG), Support Vector Machine (SVM), Vertebrae.

Full Text:

 |  (PDF views: 213)

References


  • Structures of the Vertebral Column and Thorax - Human – StudyBlue. Available from: https://www.studyblue.com/notes/note/n/structures-of-the-vertebral-column-and-thorax/ deck/7231770 Date accessed:27/08/2013.
  • Peng Z, Zhong J, Wee W, Lee JH. Automated Vertebra Detection and Segmentation from the Whole Spine MR Images. IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai. 2005. p. 2527–30.
  • Alomari RS, Corso JJ, Chaudhary V. Labeling of Lumbar Discs Using Both Pixel- and Object-Level Features With a Two-Level Probabilistic Model. IEEE Transactions on Medical Imaging. 2011 Jan; 30 (1):1–10.
  • Huang SH, Chu YH, Lai SH, Novak CL. LearningBased Vertebra Detection and Iterative Normalized-Cut Segmentation for Spinal MRI. IEEE Transactions on Medical Imaging. 2010 Oct; 28(10):1595–605.
  • Zheng Y, Nixon MS, Allen R. Automated segmentation of lumbar vertebrae in digital video fluoroscopic images. IEEE Transactions on Medical Imaging. 2004 Jan; 23(1):45–52.
  • Wong A, Mishra A, Yates J, Fieguth P, Clausi DA, Callaghan JP. Intervertebral Disc Segmentation and Volumetric Reconstruction From Peripheral Quantitative Computed Tomography Imaging. IEEE transactions on Biomedical Engineering. 2009 Nov; 56(11):2748–51.
  • Glocker B, Feulner J, Criminisi A, Haynor DR, Konukoglu E. Automatic localization and identification of vertebrae in arbitrary field of- view CT scans. Med Image Computing and Computer Assisted Intervention. 2012; (3):590–98.
  • Schmidt S, Kappes J, Bergtholdt M, Pekar V, Dries S, Bystrov D, Schnorr C. Spine detection and labeling using a parts-based graphical model. Proceedings 20th Int Conf Inf Process Med Imag. 2007; 4584. p. 122–33.
  • Dalal N,Triggs B. Histograms of oriented gradients for human detection, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), San Diego, CA, USA, 2005,1,pp .886–93.
  • Creusen IM, Wijnhoven RGJ, Herbschleb EN. de With. Color exploitation in hog-based traffic sign detection. IEEE International Conference on Image Processing, Hong Kong. 2010. p. 2669–72.
  • Lai K, Bo L, Ren X, Fox D. A large-scale hierarchical multiview RGB-D object dataset. IEEE International Conference on Robotics and Automation (ICRA), Shanghai. 2011. p. 1817–24.
  • Deniz O, Bueno G, Salido J, De la Torre F. Face recognition using Histograms of Oriented Gradients. Pattern Recognition Letters. 2011 Sep; 32(12):1598–603.
  • Bosch A, Zisserman A, Munoz X. Representing shape with a spatial pyramid kernel. International Conference on Image Video Retrieval. 2007. p. 401–08.
  • Oktay AB, Akgul YS. Simultaneous Localization of Lumbar Vertebrae and Intervertebral Discs With SVM-Based MRF. IEEE Transactions on Biomedical Engineering. 2013 Sep; 60(9):2375–83.
  • Padmapriya P, Manikandan K, Jeyanthi K, Renuga V, Sivaraman J. Detection and Classification of Brain Tumor using Radial Basis Function. Indian Journal of Science and Technology. 2016 Jan; 9(1):1–5
  • Chang CC, Lin CJ. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology. 2011; 2(3):1–39.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.