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Volume 8, Issue 3
Automated Vertebrae Extraction Using Watershed Segmentation and Tree-based Modelling Approach

Ili Ayuni Mohd Ikhsan, Aini Hussain, Mohd Asyraf Zulkifley & Aouache Mustapha

Journal of Fiber Bioengineering & Informatics, 8 (2015), pp. 547-555.

Published online: 2015-08

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  • Abstract
Vertebra segmentation and extraction are essential steps for automated vertebrae fracture assessment system. This study focuses on vertebra segmentation, which is a challenging task due to high noise and poor contrast of X-Ray images. The objective of this study is to develop and test an automated cervical vertebrae extraction to facilitate the medical researchers and physicians. The novelty of the proposed method is the combination of watershed segmentation and tree-based modelling algorithm. The proposed method has been successfully applied to a set of 50 cervical X-Ray images. Five performance metrics are calculated, which are accuracy, sensitivity, specificity, correlation and error where the best obtained results are 0.9886, 0.0655, 0.99, 0.7246 and 0.01135, respectively.
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@Article{JFBI-8-547, author = {}, title = {Automated Vertebrae Extraction Using Watershed Segmentation and Tree-based Modelling Approach}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2015}, volume = {8}, number = {3}, pages = {547--555}, abstract = {Vertebra segmentation and extraction are essential steps for automated vertebrae fracture assessment system. This study focuses on vertebra segmentation, which is a challenging task due to high noise and poor contrast of X-Ray images. The objective of this study is to develop and test an automated cervical vertebrae extraction to facilitate the medical researchers and physicians. The novelty of the proposed method is the combination of watershed segmentation and tree-based modelling algorithm. The proposed method has been successfully applied to a set of 50 cervical X-Ray images. Five performance metrics are calculated, which are accuracy, sensitivity, specificity, correlation and error where the best obtained results are 0.9886, 0.0655, 0.99, 0.7246 and 0.01135, respectively.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbim00155}, url = {http://global-sci.org/intro/article_detail/jfbi/4736.html} }
TY - JOUR T1 - Automated Vertebrae Extraction Using Watershed Segmentation and Tree-based Modelling Approach JO - Journal of Fiber Bioengineering and Informatics VL - 3 SP - 547 EP - 555 PY - 2015 DA - 2015/08 SN - 8 DO - http://doi.org/10.3993/jfbim00155 UR - https://global-sci.org/intro/article_detail/jfbi/4736.html KW - Medical Imaging KW - Cervical Vertebrae KW - Segmentation KW - Watershed KW - Tree-based Modelling AB - Vertebra segmentation and extraction are essential steps for automated vertebrae fracture assessment system. This study focuses on vertebra segmentation, which is a challenging task due to high noise and poor contrast of X-Ray images. The objective of this study is to develop and test an automated cervical vertebrae extraction to facilitate the medical researchers and physicians. The novelty of the proposed method is the combination of watershed segmentation and tree-based modelling algorithm. The proposed method has been successfully applied to a set of 50 cervical X-Ray images. Five performance metrics are calculated, which are accuracy, sensitivity, specificity, correlation and error where the best obtained results are 0.9886, 0.0655, 0.99, 0.7246 and 0.01135, respectively.
Ili Ayuni Mohd Ikhsan, Aini Hussain, Mohd Asyraf Zulkifley & Aouache Mustapha. (2019). Automated Vertebrae Extraction Using Watershed Segmentation and Tree-based Modelling Approach. Journal of Fiber Bioengineering and Informatics. 8 (3). 547-555. doi:10.3993/jfbim00155
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