We are looking for a PhD candidate who, together with our team, will substantially improve quantitative magnetic resonance imaging (
MRI) image quality using deep learning approaches.
Quantitative MRI allows healthcare providers to quantitatively assess and characterize the state of a tumour and its microenvironment. This information can be used to personalize cancer treatments. For example, a well-perfused tumour (quantified with MRI) will be more likely to react to chemotherapy than a tumour that is not perfused, as the chemo will need to reach the tumour. As personalizing a treatment based on such biomarkers can substantially improve the efficacy of the treatment, we have multiple research lines that utilize quantitative MRI at Amsterdam UMC.
However, current quantitative MRI approaches have notoriously poor image quality, low resolution and poor precision. Consequently, quantitative MRI is not used routinely in cancer care. If we can improve the image quality of quantitative MRI, it can be used in clinical routine to select the optimal treatment for each patient, greatly improving treatment outcomes worldwide.
Therefore, in this PhD-trajectory, the candidate will fundamentally change how qMRI is obtained and develop innovative explainable unsupervised physics-informed AI approaches for generating qMRI images that are of clinical quality. This will open the way to personalised treatments. These AI-driven frameworks will be tailored to suit the specific needs of qMRI. The candidate will further develop explainable AI and produce uncertainty estimates alongside the parameter maps. Finally, the candidate will test how accurately responding versus non-responding head-and-neck cancer patients receiving radiotherapy can be distinguished.
The position is financed by the NWO (TTW VIDI 2022).
Your main task will be to implement, optimize and test new approaches to AI-driven quantitative MRI.
- You will work on the entire MRI acquisition chain. You will operate state-of-the-art MRI machines (3 Tesla), acquire MRI data, write and alter the MRI-scanner software to improve the acquisition (C++), develop and perform MRI reconstructions using deep learning (Python), and analyse the MRI data;
- You, or your medical colleagues, will be scanning qMRI in head-and-neck cancer patients;
- You will conduct new academic research combining machine learning and medical physics;
- Your research will be published in reputable peer-reviewed journals. Additionally, you will regularly present your work at (international) conferences and assist in relevant teaching activities.