Students and Open positions

Master’s Thesis/ Bachelor’s Thesis/ Lab immersion

Title:

A computational algorithm for (semi-)automatic image processing for the development of targeted epidural electrical stimulation paradigms through personalized computational modelling

Student pre-requisites:

Experience with programming (C++)

Experience with image-processing

Experience/Interest in deep learning

Experience/Interest in 3D CAD modelling

Primary Supervisor:

EPFL:             Andreas Rowald, Workpackage leader (RESTORE), PhD student

IT’IS/ETHZ:    Bryn Lloyd, PhD, Project Leader Virtual Population

Project Description:

Central nervous system disorders such as spinal cord injury (SCI) and stroke lead to distinct impairments in leg motor control and balance. Epidural electrical stimulation of lumbar and sacral segments of the spinal cord has proven to restore voluntary and coordinated movements of the lower limbs in various animal models. Translation of this technology to human patients requires the development of dedicated, robust solutions for clinical use. Indeed, therapeutic success of epidural electrical stimulation entails the definition of dedicated spinal electrode arrays and stimulation strategies that can account for the large variability that is observed in clinical populations. Personalization of implantation procedures and stimulation protocols will be critical in addressing the specific motor deficits in large and diversified patient cohorts.

We are currently working in collaboration with ZurichMedTech and the IT’IS Foundation to establish a computational framework for the creation of personalized computational models to develop targeted epidural electrical stimulation strategies for the recovery of motor function after SCI. This framework has already proven to create a 1 to 1 mapping between simulation and experiment and is currently advanced to optimize stimulation paradigms. However, the extraction of anatomical features out of MRI data is slow and requires a tremendous amount of human effort. We therefore aim to develop image processing algorithms to (semi-)automatically extract key features.

Tasks:

The master’s thesis will involve the development and implementation of image processing algorithms to extract key anatomical features out of designated MRI images.

If you are interested in the project please do not hesitate to contact us: [email protected]