Fracture Detection in Traumatic Pelvic CT Images
Fracture detection in pelvic bones is vital for patient diagnostic decisions and treatment planning in traumatic pelvic injuries. Manual detection of bone fracture from computed tomography (CT) images is very challenging due to low resolution of the images and the complex pelvic structures. Automate...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2012-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2012/327198 |
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| _version_ | 1849684510116937728 |
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| author | Jie Wu Pavani Davuluri Kevin R. Ward Charles Cockrell Rosalyn Hobson Kayvan Najarian |
| author_facet | Jie Wu Pavani Davuluri Kevin R. Ward Charles Cockrell Rosalyn Hobson Kayvan Najarian |
| author_sort | Jie Wu |
| collection | DOAJ |
| description | Fracture detection in pelvic bones is vital for patient diagnostic decisions and treatment planning in traumatic pelvic injuries. Manual detection of bone fracture from computed tomography (CT) images is very challenging due to low resolution of the images and the complex pelvic structures. Automated fracture detection from segmented bones can significantly help physicians analyze pelvic CT images and detect the severity of injuries in a very short period. This paper presents an automated hierarchical algorithm for bone fracture detection in pelvic CT scans using adaptive windowing, boundary tracing, and wavelet transform while incorporating anatomical information. Fracture detection is performed on the basis of the results of prior pelvic bone segmentation via our registered active shape model (RASM). The results are promising and show that the method is capable of detecting fractures accurately. |
| format | Article |
| id | doaj-art-c0cbcc615263498f99e7079fe2a9f1f3 |
| institution | DOAJ |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-c0cbcc615263498f99e7079fe2a9f1f32025-08-20T03:23:26ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962012-01-01201210.1155/2012/327198327198Fracture Detection in Traumatic Pelvic CT ImagesJie Wu0Pavani Davuluri1Kevin R. Ward2Charles Cockrell3Rosalyn Hobson4Kayvan Najarian5Department of Computer Science, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USADepartment of Electrical and Computer Engineering, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USADepartment of Emergency Medicine, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USAVirginia Commonwealth University Reanimation Engineering Science Center (VCURES), Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USADepartment of Electrical and Computer Engineering, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USADepartment of Computer Science, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USAFracture detection in pelvic bones is vital for patient diagnostic decisions and treatment planning in traumatic pelvic injuries. Manual detection of bone fracture from computed tomography (CT) images is very challenging due to low resolution of the images and the complex pelvic structures. Automated fracture detection from segmented bones can significantly help physicians analyze pelvic CT images and detect the severity of injuries in a very short period. This paper presents an automated hierarchical algorithm for bone fracture detection in pelvic CT scans using adaptive windowing, boundary tracing, and wavelet transform while incorporating anatomical information. Fracture detection is performed on the basis of the results of prior pelvic bone segmentation via our registered active shape model (RASM). The results are promising and show that the method is capable of detecting fractures accurately.http://dx.doi.org/10.1155/2012/327198 |
| spellingShingle | Jie Wu Pavani Davuluri Kevin R. Ward Charles Cockrell Rosalyn Hobson Kayvan Najarian Fracture Detection in Traumatic Pelvic CT Images International Journal of Biomedical Imaging |
| title | Fracture Detection in Traumatic Pelvic CT Images |
| title_full | Fracture Detection in Traumatic Pelvic CT Images |
| title_fullStr | Fracture Detection in Traumatic Pelvic CT Images |
| title_full_unstemmed | Fracture Detection in Traumatic Pelvic CT Images |
| title_short | Fracture Detection in Traumatic Pelvic CT Images |
| title_sort | fracture detection in traumatic pelvic ct images |
| url | http://dx.doi.org/10.1155/2012/327198 |
| work_keys_str_mv | AT jiewu fracturedetectionintraumaticpelvicctimages AT pavanidavuluri fracturedetectionintraumaticpelvicctimages AT kevinrward fracturedetectionintraumaticpelvicctimages AT charlescockrell fracturedetectionintraumaticpelvicctimages AT rosalynhobson fracturedetectionintraumaticpelvicctimages AT kayvannajarian fracturedetectionintraumaticpelvicctimages |