The Diagnostic Image Analysis Group (http://www.diagnijmegen.nl) at the Department of Radiology, Radboud University Nijmegen Medical Centre, is offering a PhD position in a project where we collaborate with the International Institute of Information Technology in Hyderabad, India.
The Diagnostic Image Analysis Group 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 brain, breast, lung, prostate 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 twenty researchers including thirteen PhD students and support from four scientific programmers.
Blindness is affecting about 45 million people worldwide and it will double by 2020 if no action is taken. There is a marked increase in the number of people who are blind or visually impaired from eye conditions related to aging and chronic diseases, such as glaucoma, diabetic retinopathy (DR) and age-related macular degeneration (AMD). These conditions are responsible of the 85% of the number of cases of blindness in northern Europe (including the Netherlands). In India, these diseases are the second cause of blindness (after cataract) with a disproportionate share in the worldwide statistics: 12 of 45 million blind and 52 of 180 million visually impaired people are in India.
Computer-aided diagnosis (CAD) technology using retinal images has a vast potential for improving the quality of eye care while decreasing costs. See below for an example of retinal images showing signs of DR (left images) and AMD (right image). CAD systems can facilitate more health centers to be involved in the screening process for the prevention of blindness, reducing the health care costs and leading to a wider geographic coverage. However, a CAD tool for eye screening has not been established yet in clinical practice.
The overall goal of this project is to develop a web-based system where ophthalmologists or general practitioners from all over the world can upload through Internet retinal images and obtain an automatic report of the eye condition. The system must indicate in the report if the retinal image comes from an abnormal retina and, if so, whether the patient presents glaucoma, DR or AMD and in which severity grade.
A number of algorithms that are part of this overall system have already been developed in out group, see Computer-Aided Diagnosis of Retinal Images (CADR). Therefore you do not need to start from scratch. Several of these algorithms need to be improved, though. Moreover, a number of additional algorithms must be developed.
For the identification of patients with glaucoma, the system will automatically determine the optic disk area and the optic cup area. See below for an example of the optic disk and cup in a retinal image. The ratio between those areas will provide an assessment of the optic nerve cupping, an early indicator of glaucoma.
For the identification of patients with DR, eye abnormalities such as microaneurysms, hemorrhages, hard exudates, cotton wool spots or venous abnormalities need to be automatically detected. You must also develop automatic detection algorithms for drusen to identify patients with AMD. See below for an example of eye abnormalities related to DR (left) and to AMD (right).
An important part of the project is to carry out an extensive evaluation to assess how well it performs when it is introduced into eye screening programs in the Netherlands and in India.
You should be a multidisciplinary, creative and enthusiastic researcher with a 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.
As you are appointed as a PhD student, you will get 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. Clarisa Sanchez will be your dialy supervisor and she is the project leader. Bram van Ginneken will be your promotor.
This position is funded by ZonMW inside the program Medical Devices for Affordable Health. You will work at DIAG and will collaborate with our partners in India.
For more information please contact Clarisa Sanchez by e-mail.
Send applications as a single pdf file to C.SanchezGutierrez@rad.umcn.nl before May 22, 2011. This pdf file should contain your CV and a letter of motivation. In addition, the PhD candidate should provide a list of followed courses and grades and preferably a reprint of your Master thesis or any publications in English you have written.