The Diagnostic Image Analysis Group at the Department of Radiology, Radboud University Nijmegen Medical Centre, is offering a PhD position.
Optical Coherence Tomography (OCT) is an advanced image modality that stands central in diagnosis and treatment of diseases of the retina. This project focuses on the development of automated OCT analysis of retinal changes after treatment, such as the remission of fluid or abnormal thickness of the retina. Objective and precise analysis of those changes over time in OCT scans is very important for diagnosis and treatment planning and supports the understanding of the disease mechanisms.
In this project the main focus for application will be on age-related macular degeneration (AMD). AMD is the primary cause of visual impairment in industrialized countries. The recent adoption of a new treatment as the standard care of neovascular AMD since 2009 has resulted in significant visual improvement in patients. The current treatment protocol involves a monthly monitoring of treated patients in order to assess disease activity and the necessity of re-treatment. For the analysis of disease activity, the specialist evaluates retinal changes visible on OCT scans. However, this frequent monitoring of AMD patients is a difficult and cumbersome task for ophthalmologists. Therefore, automatic analysis of retinal changes seen in OCT scans may help to alleviate this bottleneck in the management of AMD and provide a fast, efficient and accurate tool for routine monitoring of patients under treatment.
The main focus of the project will be:
You should be a creative and enthusiastic researcher with an MSc degree in Computer Science, Physics, Engineering or Biomedical Sciences or similar, with a clear interest to develop image analysis algorithms and an affinity with medical topics. Good communication skills and expertise in software development, preferably in C++, are essential.
You will be appointed as a PhD student with the standard salary and secondary conditions for PhD students in the Netherlands. Your performance will be evaluated after 1 year. If the evaluation is positive, the contract will be extended by 3 years. The research should result in a PhD thesis.
The Diagnostic Image Analysis Group (DIAG) is a research division of the Department of Radiology of the Radboud University Nijmegen Medical Centre. Nijmegen is the oldest Dutch city with a rich history and one of the liveliest city centers in the Netherlands. Radboud University has over 17,000 students. Radboud University Nijmegen Medical Centre (RUNMC) is a leading academic centre for medical science, education and health care with over 8,500 staff and 3,000 students.
The focus of the Diagnostic Image Analysis group is the development and validation of novel methods in a broad range of medical imaging applications. Research topics include image analysis, image segmentation, machine learning, and the design of decision support systems. Application areas include breast imaging, prostate imaging, lung imaging, and retinal imaging. Key to the success of the group is close cooperation with clinical partners and a disease oriented approach. Currently the group consists of around 40 researchers, including 26 PhD students.
This project is part of the retina research within DIAG. This position is funded by UitZicht. The project will be performed in close collaboration with the Department of Ophthalmology of the Radboud University Nijmegen Medical center. A large database of OCT scans from both clinical practice and clinical trials is available for the research. You will be part of the DIAG team that works on retina analysis. The team consists of technical researchers and ophthalmologists and also works on automatic diabetic retinopathy screening, drusen quantification, and segmentation of normal anatomy.
For more information feel free to contact Dr. C. Sánchez by e-mail.
Send applications as a single pdf file to firstname.lastname@example.org. In this pdf file the following should be included: CV, list of followed courses and grades, letter of motivation, and preferably a reprint of your Master thesis or any publications in English you have written.