PhD Scholarship - CT and MRI Multimodal Segmentation of the Cochlea and Adjacent Anatomical Structures

The University of Melbourne is a leading international university with over 160 years of experience in teaching and research. Located in the Greater Melbourne Area, the university is committed to providing high-quality education and fostering groundbreaking research in various fields. With a strong reputation for academic excellence and innovation, the University of Melbourne offers a vibrant and inclusive environment for students and staff.

The Opportunity
Cochlear implant surgery is a well-established therapy that restores hearing of patients with severe to profound hearing loss. It has benefited more than 1 million patients worldwide. However, despite major technological advances, many challenges, such as variability of hearing performance, surgical outcomes, and risk of losing residual hearing, still remain. Introducing detailed anatomical information into the clinical workflow, from improved surgical planning and simulation through to enhanced fitting paradigms, provides an opportunity to improve hearing outcomes for many patients. To this end, this project aims to develop automated algorithms for the identification (segmentation) of anatomical structures of the temporal bone. The following tasks will be undertaken:

• Single-mode segmentation of anatomical structures of the temporal bone using CT and MR images.
• Registration and overlay of CT and MR images and development of multi-modal segmentation models.
• Cross-modality synthesis (CT to MR and vice versa) to infer structures not visible in a single mode

Scholarship Description
This is a full-time on-site role for a PhD Scholarship - CT and MRI Multimodal Segmentation of the Cochlea and Adjacent Anatomical Structures at the University of Melbourne. This scholarship is funded by Neurelec SAS (Oticon Medical), France. In this role, the successful candidate will be responsible for conducting research and developing methods for the multimodal segmentation of the cochlea and adjacent anatomical structures using CT and MRI imaging technologies. The candidate will collaborate with a multidisciplinary team of researchers and contribute to the advancement of knowledge in this area.

Qualifications

• Master's degree in machine learning
• Knowledge of deep learning algorithms
• Strong programming skills, particularly in Python
• Ability to conduct independent research and work collaboratively
• Excellent analytical and problem-solving skills
• Effective written and verbal communication skills

Desirable

• Experience in medical image analysis and segmentation
• Proficiency in CT and MRI imaging technologies
• Prior experience in cochlear imaging or related field

Note: Applications not being accepted via this website. Please submit your Expression of Interest to Dr Sudanthi Wijewickrema ([email protected])