Modeling and Features Extraction of Heel Bone Fracture Reparation Dynamical Process from X-Ray Images Based on Time Iteration Segmentation Model Driven by Gaussian Energy
Tracking of the bone reparation is one of the crucial task in the clinical traumatology. Such reparation period is conventionally subjectively observed by the clinicians. Such procedure leads to subjective errors. Therefore, mathematical model would autonomously classify respective stage of the bone healing would have significant impact to clinical practice of the traumatology. We have proposed a time deformation segmentation model based on the fitting Gaussian energy for detection and modeling of the periosteal callus which is clinically perceived as one of the dominant features determining stage of the heel bone fracture, as well as speed of the heeling. In our analysis we have compared two groups of the patients: controlled and granted group where each of them was differently loaded after placing heel bone fixator. This analysis leads to objective classification of such therapeutic procedure corresponding with the most optimal healing process.
KeywordsHeel bone Fracture Active contour Periosteal callus Fixator
The work and the contributions were supported by the project SV4508811/2101Biomedical Engineering Systems XIV’. This study was also supported by the research project The Czech Science Foundation (GACR) 2017 No. 17-03037S Investment evaluation of medical device development run at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic. This study was supported by the research project The Czech Science Foundation (TACR) ETA No. TL01000302 Medical Devices development as an effective investment for public and private entities. This article was supported by the Ministry of Education of the Czech Republic (Project No. SP2018/170). This work was supported by the European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems project, project number CZ.02.1.01/0.0/0.0/16_019/0000867 within the Operational Programme Research, Development and Education.
- 3.Kubicek, J., Penhaker, M., Oczka, D., Augustynek, M., Cerny, M., Maresova, P.: Analysis and modelling of heel bone fracture with using of active contour driven by Gaussian energy and features extraction. In: Nguyen, N.T., Hoang, D.H., Hong, T.-P., Pham, H., Trawiński, B. (eds.) ACIIDS 2018. LNCS (LNAI), vol. 10752, pp. 405–414. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75420-8_39CrossRefGoogle Scholar
- 4.Kubicek, J., Penhaker, M., Bryjova, I., Augustynek, M., Zapletal, T., Kasik, V.: Tracking of bone reparation process with using of periosteal callus extraction based on fuzzy C-means algorithm. In: Król, D., Nguyen, N.T., Shirai, K. (eds.) ACIIDS 2017. SCI, vol. 710, pp. 271–280. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56660-3_24CrossRefGoogle Scholar
- 9.Pandey, P., Guy, P., Hodgson, A.J., Abugharbieh, R.: Fast and automatic bone segmentation and registration of 3D ultrasound to CT for the full pelvic anatomy: a comparative study. Int. J. Comput. Assist. Radiol. Surg., 1–10 (2018)Google Scholar
- 11.Aouache, M., Hussain, A., Zulkifley, M.A., Wan Zaki, D.W.M., Husain, H., Abdul Hamid, H.B.: Anterior osteoporosis classification in cervical vertebrae using fuzzy decision tree. Multimed. Tools Appl. 77(3), 4011–4045 (2018)Google Scholar
- 12.Shah, R., Sharma, P.: Bone segmentation from X-Ray images: challenges and techniques. In: Bhateja, V., Nguyen, B.L., Nguyen, N.G., Satapathy, S.C., Le, D.-N. (eds.) Information Systems Design and Intelligent Applications. AISC, vol. 672, pp. 853–862. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-7512-4_84CrossRefGoogle Scholar
- 13.Liu, S., et al.: Fully automated bone mineral density assessment from low-dose chest CT. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10575, art. no. 105750 M (2018)Google Scholar
- 15.Luan, K., Liang, C., Liu, X., Li, J.: Point extraction from cross sections of fractured long bones for registration. In: 2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016, art. no. 7831955, pp. 947–951 (2017)Google Scholar
- 16.Liu, S., Xie, Y., Reeves, A.P.: Individual bone structure segmentation and labelling from low-dose chest CT. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10134, art. no. 1013444 (2017)Google Scholar
- 18.Grepl, J., Penhaker, M., Kubicek, J., Liberda, A., Mashinchi, R.: Real time signal detection and computer visualization of the patient respiration. In: Sulaiman, H.A., Othman, M.A., Othman, M.F.I., Rahim, Y.A., Pee, N.C. (eds.) Advanced Computer and Communication Engineering Technology. LNEE, vol. 362, pp. 783–793. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-24584-3_66CrossRefGoogle Scholar