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International Journal of Biomedical Imaging
Volume 2012, Article ID 327198, 10 pages
http://dx.doi.org/10.1155/2012/327198
Research Article

Fracture Detection in Traumatic Pelvic CT Images

1Department of Computer Science, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USA
2Department of Electrical and Computer Engineering, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USA
3Department of Emergency Medicine, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USA
4Virginia Commonwealth University Reanimation Engineering Science Center (VCURES), Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USA
5Department of Radiology, Virginia Commonwealth University, 401 West Main Street, Richmond, VA 23284, USA

Received 2 July 2011; Revised 30 September 2011; Accepted 30 September 2011

Academic Editor: Shan Zhao

Copyright © 2012 Jie Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [16 citations]

The following is the list of published articles that have cited the current article.

  • Eveling Castro-Gutierrez, Laura Estacio-Cerquin, Joel Gallegos-Guillen, and Javier Delgado Obando, “Detection of Acetabulum Fractures Using X-Ray Imaging and Processing Methods Focused on Noisy Images,” 2019 Amity International Conference on Artificial Intelligence (AICAI), pp. 296–302, . View at Publisher · View at Google Scholar
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  • Ling Wang, Hong Cheng, Hai Lan, Yingjie Zheng, and Kainan Li, “Automatic recognition of pertrochanteric bone fractures in femur using level sets,” 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3851–3854, . View at Publisher · View at Google Scholar
  • Pavani Davuluri, Jie Wu, Yang Tang, Charles H. Cockrell, Kevin R. Ward, Kayvan Najarian, and Rosalyn H. Hargraves, “Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries,” Computational and Mathematical Methods in Medicine, vol. 2012, pp. 1–12, 2012. View at Publisher · View at Google Scholar
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  • Mehdi Boudissa, Aurélien Courvoisier, Matthieu Chabanas, and Jérôme Tonetti, “Computer assisted surgery in preoperative planning of acetabular fracture surgery: state of the art,” Expert Review of Medical Devices, pp. 1–9, 2017. View at Publisher · View at Google Scholar
  • Matthieu Chabanas, Hadrien Oliveri, Mehdi Boudissa, and Jerome Tonetti, “Planning acetabular fracture reduction using patient-specific multibody simulation of the hip,” Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10135, 2017. View at Publisher · View at Google Scholar
  • Anees Kazi, Shadi Albarqouni, Nassir Navab, Amelia Jimenez Sanchez, Sonja Kirchhoff, Peter Biberthaler, and Diana Mateus, “Automatic classification of proximal femur fractures based on attention models,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10541, pp. 70–78, 2017. View at Publisher · View at Google Scholar
  • Joel Oswaldo Gallegos Guillen, Laura Jovani Estacio Cerquin, Javier Delgado Obando, and Eveling Castro-Gutierrez, “Segmentation of the Proximal Femur by the Analysis of X-ray Imaging Using Statistical Models of Shape and Appearance,” Artificial Intelligence and Soft Computing, vol. 10842, pp. 25–35, 2018. View at Publisher · View at Google Scholar
  • C Harriet Linda, and G Wiselin Jiji, “Hierarchical Approach to Detect Fractures in CT DICOM Images,” The Computer Journal, 2018. View at Publisher · View at Google Scholar
  • Joseph E Burns, Jianhua Yao, and Ronald M Summers, “Artificial Intelligence in Musculoskeletal Imaging: A Paradigm Shift,” Journal of Bone and Mineral Research, 2019. View at Publisher · View at Google Scholar
  • Wahyu Rahmaniar, and Wen-June Wang, “Real-Time Automated Segmentation and Classification of Calcaneal Fractures in CT Images,” Applied Sciences, vol. 9, no. 15, pp. 3011, 2019. View at Publisher · View at Google Scholar
  • Erez Yahalomi, Michael Chernofsky, and Michael Werman, “Detection of Distal Radius Fractures Trained by a Small Set of X-Ray Images and Faster R-CNN,” Intelligent Computing, vol. 997, pp. 971–981, 2019. View at Publisher · View at Google Scholar
  • Yoga Dwi Pranata, Kuan-Chung Wang, Jia-Ching Wang, Irwansyah Idram, Jiing-Yih Lai, Jia-Wei Liu, and I-Hui Hsieh, “Deep learning and SURF for automated classification and detection of calcaneus fractures in CT images,” Computer Methods and Programs in Biomedicine, 2019. View at Publisher · View at Google Scholar