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A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank
BACKGROUND: Spine magnetic resonance image (MRI) plays a very important role in the diagnosis of various spinal diseases, such as disc degeneration, scoliosis, and osteoporosis. Accurate localization and segmentation of the intervertebral disc (IVD) in spine MRI can help accelerate the diagnosis tim...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4802867/ https://www.ncbi.nlm.nih.gov/pubmed/27000749 http://dx.doi.org/10.1186/s12938-016-0146-5 |
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author | Zhu, Xinjian He, Xuan Wang, Pin He, Qinghua Gao, Dandan Cheng, Jiwei Wu, Baoming |
author_facet | Zhu, Xinjian He, Xuan Wang, Pin He, Qinghua Gao, Dandan Cheng, Jiwei Wu, Baoming |
author_sort | Zhu, Xinjian |
collection | PubMed |
description | BACKGROUND: Spine magnetic resonance image (MRI) plays a very important role in the diagnosis of various spinal diseases, such as disc degeneration, scoliosis, and osteoporosis. Accurate localization and segmentation of the intervertebral disc (IVD) in spine MRI can help accelerate the diagnosis time and assist in the treatment by providing quantitative parameters. In this paper, a method based on Gabor filter bank is proposed for IVD localization and segmentation. METHODS: First, the structural features of IVDs are extracted using a Gabor filter bank. Second, the Gabor features of spine are calculated and spinal curves are detected. Third, the Gabor feature images (GFI) of IVDs are calculated and adjusted according to the spinal curves. Fourth, the IVDs are localized by clustering analysis with GFI. Finally, an optimum grayscale-based algorithm with self-adaptive threshold, combined with the localization results and Gabor features of the spine, is performed for IVDs segmentation. RESULTS: The proposed method is verified by an MRI dataset consisting of 278 IVDs from 37 patients. The accuracy of localization is 98.23 % and the dice similarity index for segmentation evaluation is 0.9237. CONCLUSIONS: The proposed Gabor filter based method is effective for IVD localization and segmentation. It would be useful in computer-aided diagnosis of IVD diseases and computer-assisted spine surgery. |
format | Online Article Text |
id | pubmed-4802867 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48028672016-03-23 A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank Zhu, Xinjian He, Xuan Wang, Pin He, Qinghua Gao, Dandan Cheng, Jiwei Wu, Baoming Biomed Eng Online Research BACKGROUND: Spine magnetic resonance image (MRI) plays a very important role in the diagnosis of various spinal diseases, such as disc degeneration, scoliosis, and osteoporosis. Accurate localization and segmentation of the intervertebral disc (IVD) in spine MRI can help accelerate the diagnosis time and assist in the treatment by providing quantitative parameters. In this paper, a method based on Gabor filter bank is proposed for IVD localization and segmentation. METHODS: First, the structural features of IVDs are extracted using a Gabor filter bank. Second, the Gabor features of spine are calculated and spinal curves are detected. Third, the Gabor feature images (GFI) of IVDs are calculated and adjusted according to the spinal curves. Fourth, the IVDs are localized by clustering analysis with GFI. Finally, an optimum grayscale-based algorithm with self-adaptive threshold, combined with the localization results and Gabor features of the spine, is performed for IVDs segmentation. RESULTS: The proposed method is verified by an MRI dataset consisting of 278 IVDs from 37 patients. The accuracy of localization is 98.23 % and the dice similarity index for segmentation evaluation is 0.9237. CONCLUSIONS: The proposed Gabor filter based method is effective for IVD localization and segmentation. It would be useful in computer-aided diagnosis of IVD diseases and computer-assisted spine surgery. BioMed Central 2016-03-22 /pmc/articles/PMC4802867/ /pubmed/27000749 http://dx.doi.org/10.1186/s12938-016-0146-5 Text en © Zhu et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Zhu, Xinjian He, Xuan Wang, Pin He, Qinghua Gao, Dandan Cheng, Jiwei Wu, Baoming A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank |
title | A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank |
title_full | A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank |
title_fullStr | A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank |
title_full_unstemmed | A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank |
title_short | A method of localization and segmentation of intervertebral discs in spine MRI based on Gabor filter bank |
title_sort | method of localization and segmentation of intervertebral discs in spine mri based on gabor filter bank |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4802867/ https://www.ncbi.nlm.nih.gov/pubmed/27000749 http://dx.doi.org/10.1186/s12938-016-0146-5 |
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