36 months Post-Doc Position "Bone fracture reduction in trauma: A combined Deep-Learning/Statistical Shape Model approach for the estimation of the optimal reduction strategy during planning"
15 Apr 2024
Job Information
- Organisation/Company
LaTIM- Research Field
Computer science » 3 D modelling
Medical sciences » Other
Computer science » Programming- Researcher Profile
Recognised Researcher (R2)- Country
France- Application Deadline
30 May 2024 - 12:00 (Europe/Paris)- Type of Contract
Temporary- Job Status
Full-time- Offer Starting Date
1 Jun 2024- Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme- Reference Number
ANR-RHU REBONE- Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
Scientific context
Bone trauma is a global scourge and ranks as the third leading cause of overall morbidity burden according to the World Health Organization (WHO). Contrary to the scheduled orthopedic surgery that benefits from recent efficient edge-cutting digital technologies, trauma constraints are higher with a shorter period of management, a high complexity and multiplicity of treated cases and a greater variability of the surgeon experience. To this end, a funded research project “ReBone” (ANR RHU, 24M€) gathering several industrial, academic, and medical partners have been recently launched. The aim is to optimize the surgery and to minimize complications in complex bone trauma by developing and validating personalized, automated, and collaborative pre-operative planning solutions, and by providing intraoperative solutions allowing the accurate execution of the planning during surgery. “ReBone” will provide thus a fundamental, deep, and continuous improvement in clinical and surgical management of severe trauma and complex fractures, to (1) reduce treatment delays, (2) have access to more precise and reproducible guided surgeries, (3) decrease post-operative complications. The Laboratory of Medical Information Processing (LaTIM ) will be in charge of the fracture reduction modelling and the simulation of the hardware fixation. Still today, most of the available commercial solutions to plan bone fracture reduction rely only on manual approaches which is hardly acceptable for the surgeon especially when the number of fractures to be treated becomes too large [1]. Our aim is therefore to provide a complete easy-to-use planning software solution allowing the automatic and fast simulation of both the fracture reduction and the hardware fixation based on geometrical criteria.
Mission
Most of the existing methods for the simulation of the fracture reduction are based on the incorporation of the mirrored healthy contralateral bone [2-5]. But these methods cannot be automatically used in all patients, especially in cases of natural shape differences or bilateral trauma [6]. Others approaches based on the usual registration algorithms have been also proposed to estimate the reduction process from the alignment of the fracture lines, but their performances were very dependent on the quality of the initialization [7-9]. Statistical Shape Models (SSMs) have been also recently introduced [6, 10]. Although SSMs do not require contralateral bones and can better drive the estimation of the fracture alignment, the accuracy of the estimation is very dependent on the classes and types of fractures success. We want therefore to propose a generic approach allowing the accurate, robust, and fast simulation of the optimal fracture reduction strategy whatever the type and class of the fracture. Combined approaches exploiting both Deep-Learning and shape priors will be investigated to overcome current limitations [11]. Specific SSMs will be thus created for the most significant fracture sites (distal radius, acetabular and tibial plateau fractures) and learning approaches will be employed to drive the reduction process according to the SSM whatever the fracture classification. Validation will be performed by comparing the automatic reduction with manual reductions proposed by surgeons on real data. An integration of the proposed approach will be finally integrated, in collaboration with engineers, inside our planning software to be used by surgeons.
Environment
This post-doc position will be hosted in the LaTIM. Born from the complementarity between health and data science, the LaTIM laboratory develops multi-disciplinary research driven by members from IMT Atlantique, CHRU Brest, University of Western Brittany and Inserm. The recruited postdoc will work in collaboration with academic, industrial and hospital partners within the context of the RHU Rebone project. Access will be given to clinical data from our clinical partners as well as to the PLaTIMed platform (https://platimed.fr/ ) to make realistic evaluation of the proposed approaches.
Application
CV with list of publications, cover letter and two letters of recommendation, have to be sent to Guillaume Dardenne ([email protected] ) and Valérie Burdin ([email protected] ).
The position is available as soon as possible for three years.
The salary will depend on the candidate’s experience.
References
[1] Moolenaar, J., Tümer, N., & Checa, S. (2022). Computer-assisted preoperative planning of bone fracture fixation surgery: A state-of-the-art review.
[2] Casari, F. A., Roner, S., Fürnstahl, P., Nagy, L., & Schweizer, A. (2021). Computer-assisted open reduction internal fixation of intraarticular radius fractures navigated with patient-specific instrumentation, a prospective case series. Archives of Orthopaedic and Trauma Surgery, 141, 1425-1432.
[3] Zhao, C., Guan, M., Shi, C., Zhu, G., Gao, X., Zhao, X., ... & Wu, X. (2022). Automatic reduction planning of pelvic fracture based on symmetry. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 10(6), 577-584.
[4] Okada, T., Iwasaki, Y., Koyama, T., Sugano, N., Chen, Y. W., Yonenobu, K., & Sato, Y. (2008). Computer-assisted preoperative planning for reduction of proximal femoral fracture using 3-D-CT data. IEEE Transactions on Biomedical Engineering, 56(3), 749-759.
[5] Fürnstahl, P., Székely, G., Gerber, C., Hodler, J., Snedeker, J. G., & Harders, M. (2012). Computer assisted reconstruction of complex proximal humerus fractures for preoperative planning. Medical image analysis, 16(3), 704-720.
[6] Han, R., Uneri, A., Vijayan, R. C., Wu, P., Vagdargi, P., Sheth, N., ... & Siewerdsen, J. H. (2021). Fracture reduction planning and guidance in orthopaedic trauma surgery via multi-body image registration. Medical image analysis, 68, 101917.
[7] Thomas, T. P. (2010). Virtual pre-operative reconstruction planning for comminuted articular fractures (Doctoral dissertation, University of Iowa).
[8] Liu, B., Zhang, S., Zhang, J., Xu, Z., Chen, Y., Liu, S., ... & Yang, L. (2019). A personalized preoperative modeling system for internal fixation plates in long bone fracture surgery—A straightforward way from CT images to plate model. The International Journal of Medical Robotics and Computer Assisted Surgery, 15(5), e2029.
[9] Paulano-Godino, F. & Jiménez-Delgado, J.J. (2017). Identification of fracture zones and its application in automatic bone fracture reduction. Computer Methods and Programs in Biomedicine, 141, 93-104.
[10] Fouefack J.-R., Borotikar B., Lüthi M., Douglas T. S., Burdin V., Mutsvangwa T. E.M. (2023). Dynamic multi feature-class Gaussian process models. Medical Image Analysis, 85 (10.1016/j.media.2022.102730 ).
[11] Boutillon A., Borotikar B., Burdin V., Conze P.H. (2022). Multi-structure bone segmentation in pediatric MR images with combined regularization from shape priors and adversarial network. Artificial Intelligence in Medicine, 132 (10.1016/j.artmed.2022.102364 ).
Requirements
- Research Field
- Computer science » 3 D modelling
- Education Level
- PhD or equivalent
Skills/Qualifications
PhD in computer vision, AI, applied mathematics.
Good programming skills is an important requisite, especially in python and C++. Autonomy, open-mindedness, and motivation
Good English skills are also expected.
- Languages
- ENGLISH
- Level
- Good
- Research Field
- Computer science » 3 D modellingComputer science » Programming
- Years of Research Experience
- 1 - 4
Additional Information
Work Location(s)
- Number of offers available
- 1
- Company/Institute
- LaTIM
- Country
- France
- City
- Brest
- Geofield
Where to apply
[email protected]
Contact
- State/Province
Brittany- City
Brest- Website
https://nouveau.univ-brest.fr/latim/en- Street
LaTIM, Faculté de Médecine, 22 Avenue Camille Desmoulins, Bâtiment IBRBS, étage 1- Postal Code
29238
STATUS: EXPIRED