Register now After registration you will be able to apply for this opportunity online.
Camera-based motion correction for cerebrovascular 4D flow MRI using neuromorphic and computer vision approaches
The aim of this project is to develop a camera-based solution for motion correction of cerebrovascular 4D flow MRI, including hardware development and (deep learning-based) data analysis.
Phase Contrast Cardiovascular Magnetic Resonance MR Imaging (PC-MRI) allows for the subject specific quantitative assessment of blood flow, with cerebrovascular applications including dementia, aneurysms, arteriovenous malformations, and atherosclerosis among others. However, the required high spatial resolution (~0.8 mm3) to assess smaller vessels results in a high sensitivity to subject motion (random but also breathing). To overcome this issue, sub-voxel motion during acquisition can be measured using a camera, which can be used to retrospectively correct the data before image reconstruction.
Application: https://doi.org/10.1016/j.neuroimage.2022.119711
Methods overview: http://dx.doi.org/10.1088/0031-9155/61/5/R32
Phase Contrast Cardiovascular Magnetic Resonance MR Imaging (PC-MRI) allows for the subject specific quantitative assessment of blood flow, with cerebrovascular applications including dementia, aneurysms, arteriovenous malformations, and atherosclerosis among others. However, the required high spatial resolution (~0.8 mm3) to assess smaller vessels results in a high sensitivity to subject motion (random but also breathing). To overcome this issue, sub-voxel motion during acquisition can be measured using a camera, which can be used to retrospectively correct the data before image reconstruction. Application: https://doi.org/10.1016/j.neuroimage.2022.119711 Methods overview: http://dx.doi.org/10.1088/0031-9155/61/5/R32
The aim of this project is to develop a camera-based solution for motion correction of cerebrovascular 4D flow MRI. The student will investigate the possible setups proposed in literature, assemble the hardware of the camera-based solution, develop the data processing software (with the possibility to explore denoising algorithms), and test in-vivo using a 3T MRI.
The aim of this project is to develop a camera-based solution for motion correction of cerebrovascular 4D flow MRI. The student will investigate the possible setups proposed in literature, assemble the hardware of the camera-based solution, develop the data processing software (with the possibility to explore denoising algorithms), and test in-vivo using a 3T MRI.
Supervisors: Manuel Christanell (mchristanel@ethz.ch) and Luuk Jacobs (ljacobs@ethz.ch). To apply for this project please email a copy of your CV and transcripts of your Bachelor and/or Master studies.
Supervisors: Manuel Christanell (mchristanel@ethz.ch) and Luuk Jacobs (ljacobs@ethz.ch). To apply for this project please email a copy of your CV and transcripts of your Bachelor and/or Master studies.