University Post
University of Copenhagen
Independent of management

Ph.d.-forsvar

PhD defence by Faezeh Moshfeghifar

Ph.d.-forsvar — On 23 May 2022, Faezeh Moshfeghifar will defend her PhD thesis titled 'Hip Joint Finite Element Modeling'.

Info

Date & Time:

Place:
SCI-DIKU-UP1-1-1-N116A & SCI-DIKU-UP1-1-1-N116B

Hosted by:
Department of Computer Science

Cost:
Free

Abstract

Population-based finite element analysis of hip joint models enables us to study the effect of inter-subject variability on the simulation results. This approach is the dawn of computerized clinical trials and offers various contributions to improving current clinical treatment, the design of surgical simulators for virtual training, and optimizing hip implants.

Despite the broad application of population-based analyses, developing large-scale subject-specific models is a challenging task and requires extensive manual effort. Thus, most state-of-the-art studies are limited in the number of subjects, and the anatomical representations are often subjected to simplifications.

This thesis provides novel methods for developing finite element models that enable large-scale population-based assessment of hip joint behavior. We benefit from the power of computer science to improve the quality and automate the standard modeling approaches. We further employ our new pipeline to generate multiple subject-specific finite element models of the bones and cartilages in the hip joint area. The subject-specific finite element models are clinically validated and have high-quality discretization with accurate geometries.

Our work is one of the largest model repositories concerning the number of subjects and regions of interest. We aim to empower researchers with free access to verified and reproducible computational models. Thus, our detailed research data, including the clinical images, the segmentation label maps, the finite element models, and software tools, are openly accessible on https://diku-dk.github.io/libhip. In future work, we aim to add additional structures to our models and upscale the population size as a direct benefit of our approach.

Supervisors

Principal Supervisor Kenny Erleben

Co-Supervisor Sune Darkner


Assessment Committee

Professor Erik Bjørnager Dam, Department of Computer Science, UCPH

Professor John Rasmussen, Department of Materials and Production, Aalborg University

Professor Marleen de Bruijne , Department of Radiology and Nuclear Medicine of Erasmus MC, University Medical Center Rotterdam

Moderator of defence

Associate Professor Bulat Ibragimov, Department of Computer Science

For a digital copy of the thesis, please visit https://di.ku.dk/english/research/phd/.

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