Abstract
The X-ray examination can effectively help for the diagnosis and analysis of spinal diseases because it possesses the properties of fast, non-invasive, low radiation dose and low cost. In order to obtain the valuable quantitative information of the spine, the automated computer aided tools are developed. The segmentation of vertebrae is an important step to analyze the disease severity from the spinal X-ray images. Although there were numerous studies for automatic vertebrae segmentation in the literature, the segmentation of vertebrae from the frontal X-ray images is still a challenging topic. In this paper, a hybrid method is proposed to segment the thoracic and lumbar vertebrae from an anteroposterior (AP) full spine X-ray image. We apply image processing techniques to detect the vertebral regions and then use the convolutional neural network (CNN) to segment the vertebrae. The segmentation performance using the proposed method is remarkably high with DSC value of 0.941.
| Original language | English |
|---|---|
| Title of host publication | IHIP 2018 - 2018 International Conference on Information Hiding and Image Processing |
| Publisher | Association for Computing Machinery |
| Pages | 57-61 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781450365468 |
| DOIs | |
| Publication status | Published - 2018 Sep 22 |
| Event | 1st International Conference on Information Hiding and Image Processing, IHIP 2018 - Manchester, United Kingdom Duration: 2018 Sep 22 → 2018 Sep 24 |
Publication series
| Name | ACM International Conference Proceeding Series |
|---|
Conference
| Conference | 1st International Conference on Information Hiding and Image Processing, IHIP 2018 |
|---|---|
| Country | United Kingdom |
| City | Manchester |
| Period | 18-09-22 → 18-09-24 |
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All Science Journal Classification (ASJC) codes
- Software
- Human-Computer Interaction
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
Cite this
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Vertebrae segmentation from X-ray images using convolutional neural network. / Fu, Min Jun; Lin, Chii-Jeng; Sun, Yung-Nien; Kuok, Chan Pang; Horng, Ming Huwi.
IHIP 2018 - 2018 International Conference on Information Hiding and Image Processing. Association for Computing Machinery, 2018. p. 57-61 (ACM International Conference Proceeding Series).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Vertebrae segmentation from X-ray images using convolutional neural network
AU - Fu, Min Jun
AU - Lin, Chii-Jeng
AU - Sun, Yung-Nien
AU - Kuok, Chan Pang
AU - Horng, Ming Huwi
PY - 2018/9/22
Y1 - 2018/9/22
N2 - The X-ray examination can effectively help for the diagnosis and analysis of spinal diseases because it possesses the properties of fast, non-invasive, low radiation dose and low cost. In order to obtain the valuable quantitative information of the spine, the automated computer aided tools are developed. The segmentation of vertebrae is an important step to analyze the disease severity from the spinal X-ray images. Although there were numerous studies for automatic vertebrae segmentation in the literature, the segmentation of vertebrae from the frontal X-ray images is still a challenging topic. In this paper, a hybrid method is proposed to segment the thoracic and lumbar vertebrae from an anteroposterior (AP) full spine X-ray image. We apply image processing techniques to detect the vertebral regions and then use the convolutional neural network (CNN) to segment the vertebrae. The segmentation performance using the proposed method is remarkably high with DSC value of 0.941.
AB - The X-ray examination can effectively help for the diagnosis and analysis of spinal diseases because it possesses the properties of fast, non-invasive, low radiation dose and low cost. In order to obtain the valuable quantitative information of the spine, the automated computer aided tools are developed. The segmentation of vertebrae is an important step to analyze the disease severity from the spinal X-ray images. Although there were numerous studies for automatic vertebrae segmentation in the literature, the segmentation of vertebrae from the frontal X-ray images is still a challenging topic. In this paper, a hybrid method is proposed to segment the thoracic and lumbar vertebrae from an anteroposterior (AP) full spine X-ray image. We apply image processing techniques to detect the vertebral regions and then use the convolutional neural network (CNN) to segment the vertebrae. The segmentation performance using the proposed method is remarkably high with DSC value of 0.941.
UR - http://www.scopus.com/inward/record.url?scp=85061546782&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061546782&partnerID=8YFLogxK
U2 - 10.1145/3292425.3293463
DO - 10.1145/3292425.3293463
M3 - Conference contribution
AN - SCOPUS:85061546782
T3 - ACM International Conference Proceeding Series
SP - 57
EP - 61
BT - IHIP 2018 - 2018 International Conference on Information Hiding and Image Processing
PB - Association for Computing Machinery
ER -