Semi-automated vertebral segmentation of human spine in MRI images

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Image segmentation is an important task in medical image processing to assist physicians or radiologists in making faster and effective diagnosis and treatment. However, there is still lack of effective segmentation methods to extract human spine in Magnetic resonance imaging (MRI) images. In this study, we propose a segmentation method using 12-anatomical point representation (12-APR) method for human spine vertebra. The proposed method is a semi-automatic segmentation in which 12-points will be manually annotated on the region of interest (ROI) before the ROI can be extracted automatically. The performance of this segmentation is evaluated using six performance metrics and the results show that the proposed method gives the highest accuracy (99.87%), specificity (99.89%), Dice similarity coefficient (94.04%), Jaccard similarity coefficient (88.81%) and Cosine similarity coefficient (94.14%).

Original languageEnglish
Title of host publication2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages120-124
Number of pages5
ISBN (Electronic)9781509028894
DOIs
Publication statusPublished - 27 Mar 2017
Event2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016 - Putrajaya, Malaysia
Duration: 14 Nov 201616 Nov 2016

Other

Other2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
CountryMalaysia
CityPutrajaya
Period14/11/1616/11/16

Fingerprint

Medical image processing
spine
Image segmentation
Magnetic resonance imaging
magnetic resonance
coefficients
vertebrae
physicians
image processing

Keywords

  • Accuracy
  • MRI
  • Segmentation
  • Sensitivity
  • Similarity coefficient
  • Specificity
  • Spine

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Biomedical Engineering
  • Control and Systems Engineering
  • Hardware and Architecture
  • Computer Networks and Communications
  • Instrumentation

Cite this

Ling, C. S., Mimi Diyana, W., Wan Zaki, W. M. D., Hussain, A., & Abdul Hamid, H. (2017). Semi-automated vertebral segmentation of human spine in MRI images. In 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016 (pp. 120-124). [7888021] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAEES.2016.7888021

Semi-automated vertebral segmentation of human spine in MRI images. / Ling, C. S.; Mimi Diyana, W.; Wan Zaki, Wan Mimi Diyana; Hussain, Aini; Abdul Hamid, Hamzaini.

2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 120-124 7888021.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ling, CS, Mimi Diyana, W, Wan Zaki, WMD, Hussain, A & Abdul Hamid, H 2017, Semi-automated vertebral segmentation of human spine in MRI images. in 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016., 7888021, Institute of Electrical and Electronics Engineers Inc., pp. 120-124, 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016, Putrajaya, Malaysia, 14/11/16. https://doi.org/10.1109/ICAEES.2016.7888021
Ling CS, Mimi Diyana W, Wan Zaki WMD, Hussain A, Abdul Hamid H. Semi-automated vertebral segmentation of human spine in MRI images. In 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 120-124. 7888021 https://doi.org/10.1109/ICAEES.2016.7888021
Ling, C. S. ; Mimi Diyana, W. ; Wan Zaki, Wan Mimi Diyana ; Hussain, Aini ; Abdul Hamid, Hamzaini. / Semi-automated vertebral segmentation of human spine in MRI images. 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 120-124
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