Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function

Ala Al Kafri; Sud Sudirman; Abir J. Hussain; Paul Fergus; Dhiya Al-Jumeily; Hiba Al Smadi; Mohammed Khalaf; Mohammed Al-Jumaily; Wasfi Al-Rashdan; Mohammad Bashtawi

doi:10.1109/DeSE.2017.20

Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function

Ala Al Kafri, Sud Sudirman, Abir J. Hussain, Paul Fergus, Dhiya Al-Jumeily, Hiba Al Smadi, Mohammed Khalaf, Mohammed Al-Jumaily, Wasfi Al-Rashdan, Mohammad Bashtawi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Disc herniation is considered as the main cause for lower back pain (LBP), a health issue that affects a very high proportion of the UK population and is costing the UK government over £1.3 million per day in health care cost. Currently, the process to diagnose the cause of LBP involves a visual examination of a large number of Magnetic Resonance Images (MRI) but this process is both expensive in terms time and effort. Automatic detection of the lumbar disc herniation will reduce the time to diagnose and detect the cause of LBP by the orthopedist. There has been very limited progress towards automatic detection of disc herniation and all of the proposed techniques still require substantial manual intervention in many of the stages. Our analysis of the problem suggests that using the axial view of the MRI could potentially improve the outcome as opposed to the sagittal view used by these techniques. In this paper, we propose using the Centroid Distance Function as a shape feature of a segmented disc MRI taken from the axial view. Visual observation of the feature indicates that the feature could be used as a suitable indicator of the presence of herniation in the lumbar disc.

Original language	English
Title of host publication	Proceedings - International Conference on Developments in eSystems Engineering, DeSE
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	9-13
Number of pages	5
ISBN (Print)	9781538617212
DOIs	https://doi.org/10.1109/DeSE.2017.20
Publication status	Published - 7 Feb 2018
Event	10th International Conference on Developments in eSystems Engineering (DeSE) - Paris, France Duration: 14 Jun 2017 → 16 Jun 2017

Publication series

Name	Proceedings - International Conference on Developments in eSystems Engineering, DeSE

Conference

Conference	10th International Conference on Developments in eSystems Engineering (DeSE)
Country/Territory	France
City	Paris
Period	14/06/17 → 16/06/17

Access to Document

10.1109/DeSE.2017.20

Cite this

Al Kafri, A., Sudirman, S., Hussain, A. J., Fergus, P., Al-Jumeily, D., Smadi, H. A., Khalaf, M., Al-Jumaily, M., Al-Rashdan, W., & Bashtawi, M. (2018). Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function. In Proceedings - International Conference on Developments in eSystems Engineering, DeSE (pp. 9-13). (Proceedings - International Conference on Developments in eSystems Engineering, DeSE). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DeSE.2017.20

Al Kafri, Ala ; Sudirman, Sud ; Hussain, Abir J. et al. / Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function. Proceedings - International Conference on Developments in eSystems Engineering, DeSE. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 9-13 (Proceedings - International Conference on Developments in eSystems Engineering, DeSE).

@inproceedings{8123b97ffb754f8cab2014fff94c6faa,

title = "Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function",

abstract = "Disc herniation is considered as the main cause for lower back pain (LBP), a health issue that affects a very high proportion of the UK population and is costing the UK government over £1.3 million per day in health care cost. Currently, the process to diagnose the cause of LBP involves a visual examination of a large number of Magnetic Resonance Images (MRI) but this process is both expensive in terms time and effort. Automatic detection of the lumbar disc herniation will reduce the time to diagnose and detect the cause of LBP by the orthopedist. There has been very limited progress towards automatic detection of disc herniation and all of the proposed techniques still require substantial manual intervention in many of the stages. Our analysis of the problem suggests that using the axial view of the MRI could potentially improve the outcome as opposed to the sagittal view used by these techniques. In this paper, we propose using the Centroid Distance Function as a shape feature of a segmented disc MRI taken from the axial view. Visual observation of the feature indicates that the feature could be used as a suitable indicator of the presence of herniation in the lumbar disc.",

author = "{Al Kafri}, Ala and Sud Sudirman and Hussain, {Abir J.} and Paul Fergus and Dhiya Al-Jumeily and Smadi, {Hiba Al} and Mohammed Khalaf and Mohammed Al-Jumaily and Wasfi Al-Rashdan and Mohammad Bashtawi",

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doi = "10.1109/DeSE.2017.20",

language = "English",

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note = "10th International Conference on Developments in eSystems Engineering (DeSE) ; Conference date: 14-06-2017 Through 16-06-2017",

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Al Kafri, A, Sudirman, S, Hussain, AJ, Fergus, P, Al-Jumeily, D, Smadi, HA, Khalaf, M, Al-Jumaily, M, Al-Rashdan, W & Bashtawi, M 2018, Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function. in Proceedings - International Conference on Developments in eSystems Engineering, DeSE. Proceedings - International Conference on Developments in eSystems Engineering, DeSE, Institute of Electrical and Electronics Engineers Inc., pp. 9-13, 10th International Conference on Developments in eSystems Engineering (DeSE), Paris, France, 14/06/17. https://doi.org/10.1109/DeSE.2017.20

Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function. / Al Kafri, Ala; Sudirman, Sud; Hussain, Abir J. et al.
Proceedings - International Conference on Developments in eSystems Engineering, DeSE. Institute of Electrical and Electronics Engineers Inc., 2018. p. 9-13 (Proceedings - International Conference on Developments in eSystems Engineering, DeSE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function

AU - Al Kafri, Ala

AU - Sudirman, Sud

AU - Hussain, Abir J.

AU - Fergus, Paul

AU - Al-Jumeily, Dhiya

AU - Smadi, Hiba Al

AU - Khalaf, Mohammed

AU - Al-Jumaily, Mohammed

AU - Al-Rashdan, Wasfi

AU - Bashtawi, Mohammad

PY - 2018/2/7

Y1 - 2018/2/7

N2 - Disc herniation is considered as the main cause for lower back pain (LBP), a health issue that affects a very high proportion of the UK population and is costing the UK government over £1.3 million per day in health care cost. Currently, the process to diagnose the cause of LBP involves a visual examination of a large number of Magnetic Resonance Images (MRI) but this process is both expensive in terms time and effort. Automatic detection of the lumbar disc herniation will reduce the time to diagnose and detect the cause of LBP by the orthopedist. There has been very limited progress towards automatic detection of disc herniation and all of the proposed techniques still require substantial manual intervention in many of the stages. Our analysis of the problem suggests that using the axial view of the MRI could potentially improve the outcome as opposed to the sagittal view used by these techniques. In this paper, we propose using the Centroid Distance Function as a shape feature of a segmented disc MRI taken from the axial view. Visual observation of the feature indicates that the feature could be used as a suitable indicator of the presence of herniation in the lumbar disc.

AB - Disc herniation is considered as the main cause for lower back pain (LBP), a health issue that affects a very high proportion of the UK population and is costing the UK government over £1.3 million per day in health care cost. Currently, the process to diagnose the cause of LBP involves a visual examination of a large number of Magnetic Resonance Images (MRI) but this process is both expensive in terms time and effort. Automatic detection of the lumbar disc herniation will reduce the time to diagnose and detect the cause of LBP by the orthopedist. There has been very limited progress towards automatic detection of disc herniation and all of the proposed techniques still require substantial manual intervention in many of the stages. Our analysis of the problem suggests that using the axial view of the MRI could potentially improve the outcome as opposed to the sagittal view used by these techniques. In this paper, we propose using the Centroid Distance Function as a shape feature of a segmented disc MRI taken from the axial view. Visual observation of the feature indicates that the feature could be used as a suitable indicator of the presence of herniation in the lumbar disc.

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M3 - Conference contribution

SN - 9781538617212

T3 - Proceedings - International Conference on Developments in eSystems Engineering, DeSE

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EP - 13

BT - Proceedings - International Conference on Developments in eSystems Engineering, DeSE

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th International Conference on Developments in eSystems Engineering (DeSE)

Y2 - 14 June 2017 through 16 June 2017

ER -

Al Kafri A, Sudirman S, Hussain AJ, Fergus P, Al-Jumeily D, Smadi HA et al. Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function. In Proceedings - International Conference on Developments in eSystems Engineering, DeSE. Institute of Electrical and Electronics Engineers Inc. 2018. p. 9-13. (Proceedings - International Conference on Developments in eSystems Engineering, DeSE). doi: 10.1109/DeSE.2017.20

Detecting the Disc Herniation in Segmented Lumbar Spine MR Image Using Centroid Distance Function

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