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Atlas-based segmentation of degenerated lumbar intervertebral discs from MR images of the spine

Atlas-based segmentation of degenerated lumbar intervertebral discs from MR images of the spine
Atlas-based segmentation of degenerated lumbar intervertebral discs from MR images of the spine
Intervertebral disc degeneration is an age-associated condition related to chronic back pain, while its consequences are responsible for over 90% of spine surgical procedures. In clinical practice, MRI is the modality of reference for diagnosing disc degeneration. In this study, we worked toward 2-D semiautomatic segmentation of both normal and degenerated lumbar intervertebral discs from T2-weighted midsagittal MR images of the spine. This task is challenged by partial volume effects and overlapping gray-level values between neighboring tissue classes. To overcome these problems three variations of atlas-based segmentation using a probabilistic atlas of the intervertebral disc were developed and their accuracies were quantitatively evaluated against manually segmented data. The best overall performance, when considering the tradeoff between segmentation accuracy and time efficiency, was accomplished by the atlas-robust-fuzzy c-means approach, which combines prior anatomical knowledge by means of a rigidly registered probabilistic disc atlas with fuzzy clustering techniques incorporating smoothness constraints. The dice similarity indexes of this method were 91.6% for normal and 87.2% for degenerated discs. Research in progress utilizes the proposed approach as part of a computer-aided diagnosis system for quantification and characterization of disc degeneration severity. Moreover, this approach could be exploited in computer-assisted spine surgery. © 2006 IEEE.
Disc degeneration, Image segmentation, Intervertebral discs, MRI
0018-9294
2225-2231
Michopoulou, Sofia K.
f21ba2a3-f5d3-4998-801f-1ae72ff5d92c
Costaridou, Lena
aa571944-616a-40c6-b5c0-3db0d7efa9f1
Panagiotopoulos, Elias
91f90d97-2047-4fd2-9e29-2346da1982e8
Speller, Robert
f2001a5e-435f-45ee-8e2d-c7d2c8168f4a
Panayiotakis, George
6f7b13c8-b9c6-4c0e-9e72-bd5c72aa1065
Todd-Pokropek, Andrew
309d666b-7b34-4a79-ac94-653bc71c0099
Michopoulou, Sofia K.
f21ba2a3-f5d3-4998-801f-1ae72ff5d92c
Costaridou, Lena
aa571944-616a-40c6-b5c0-3db0d7efa9f1
Panagiotopoulos, Elias
91f90d97-2047-4fd2-9e29-2346da1982e8
Speller, Robert
f2001a5e-435f-45ee-8e2d-c7d2c8168f4a
Panayiotakis, George
6f7b13c8-b9c6-4c0e-9e72-bd5c72aa1065
Todd-Pokropek, Andrew
309d666b-7b34-4a79-ac94-653bc71c0099

Michopoulou, Sofia K., Costaridou, Lena, Panagiotopoulos, Elias, Speller, Robert, Panayiotakis, George and Todd-Pokropek, Andrew (2009) Atlas-based segmentation of degenerated lumbar intervertebral discs from MR images of the spine. IEEE Transactions on Biomedical Engineering, 56 (9), 2225-2231. (doi:10.1109/TBME.2009.2019765).

Record type: Article

Abstract

Intervertebral disc degeneration is an age-associated condition related to chronic back pain, while its consequences are responsible for over 90% of spine surgical procedures. In clinical practice, MRI is the modality of reference for diagnosing disc degeneration. In this study, we worked toward 2-D semiautomatic segmentation of both normal and degenerated lumbar intervertebral discs from T2-weighted midsagittal MR images of the spine. This task is challenged by partial volume effects and overlapping gray-level values between neighboring tissue classes. To overcome these problems three variations of atlas-based segmentation using a probabilistic atlas of the intervertebral disc were developed and their accuracies were quantitatively evaluated against manually segmented data. The best overall performance, when considering the tradeoff between segmentation accuracy and time efficiency, was accomplished by the atlas-robust-fuzzy c-means approach, which combines prior anatomical knowledge by means of a rigidly registered probabilistic disc atlas with fuzzy clustering techniques incorporating smoothness constraints. The dice similarity indexes of this method were 91.6% for normal and 87.2% for degenerated discs. Research in progress utilizes the proposed approach as part of a computer-aided diagnosis system for quantification and characterization of disc degeneration severity. Moreover, this approach could be exploited in computer-assisted spine surgery. © 2006 IEEE.

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More information

e-pub ahead of print date: 14 April 2009
Keywords: Disc degeneration, Image segmentation, Intervertebral discs, MRI

Identifiers

Local EPrints ID: 487909
URI: http://eprints.soton.ac.uk/id/eprint/487909
ISSN: 0018-9294
PURE UUID: 6d262961-758b-4ba1-845e-4174dc8845a5

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Date deposited: 08 Mar 2024 18:05
Last modified: 17 Mar 2024 07:57

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Contributors

Author: Sofia K. Michopoulou
Author: Lena Costaridou
Author: Elias Panagiotopoulos
Author: Robert Speller
Author: George Panayiotakis
Author: Andrew Todd-Pokropek

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