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CBIR-DSN: integrating clustering and retrieval platforms for disk space narrowing degradation assessment

  • Aouache MustaphaEmail author
  • Aini Hussain
  • Wan Siti Halimatul Munirah Wan Ahmad
  • Wan Mimi Diyana Wan Zaki
  • Hamzaini Bin Abdul Hamid
Article
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Abstract

A system that is capable of assessing spine osteoarthritis conditions which affect a significant portion of the elderly population could be very valuable to radiologists, researchers of arthritis and musculoskeletal diseases, and educators. To this end, there is very limited research published in the literature concerning the degradation assessment of spinal intervertebral disc space narrowing (DSN). Thus, this paper intends to develop a system that focuses on assessing the degradation of disk space narrowing (DSN) to assist in radiologist’s decision-making in the characterization of cervical and lumbar images. A novel experiment based on our previous research (Aouache et al. 2009; Aouache et al. Biomed Eng Online 14(1):6, 2015) was conducted by integrating clustering and retrieval platforms to achieve this objective. Two shape boundary, 9-points, and B-spline have been used as the foundation for DSN model construction using active shape model. The segmented DSNs have then indexed via region and contour-based features descriptor. For better efficiency, clustering using a vocabulary tree model (VTM) is constructed to identify correct DSN cluster and build multi-clusters subsets for faster and robust retrieval research process. Our system achieved an accuracy of average retrieval rate (ARR) more than 90% and 88% for cervical and lumbar data set accordingly. We expect the proposed system will assist in decision-making and uses by radiologists or researchers for further investigation.

Keywords

Spine radiography Disk space narrowing Modeling Indexing approach VTM clustering DSN retrieval 

Notes

Acknowledgements

This work is supported in parts by the Ministry of Science, Technology, and Innovation and Centre for Integrated Systems Engineering and Advanced Technologies (INTEGRA), Universiti Kebangsaan Malaysia (project code: DIP-2018- 020) along with the collaboration and participation of SIA research team, Division Telecom, CDTA, Algeria.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Division TélécomCentre de Développement des Technologies Avancées (CDTA)Baba HassenAlgeria
  2. 2.Centre for Integrated Systems Engineering and Advanced Technologies (INTEGRA), Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan MalaysiaSelangorMalaysia
  3. 3.Department of Radiology, Faculty of MedicineUniversiti Kebangsaan MalaysiaSelangorMalaysia

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