WALK-IN INTERVIEW 2017 MASTER AND PHD INTAKE AT CISIR, UTP
10th JUNE 2017, SaturdayCAPE, Level 16, Menara 2, Menara Kembar Bank Rakyat, Jalan Travers, Kuala Lumpur09:00 - 16:00
BRING YOUR RESUME AND ACADEMIC CERTIFICATES
(For International Student, we will have Skype Interview for later date)
The Department of Electrical & Electronic Engineering, and the Centre for Intelligent Signal and Imaging Research (CISIR) strongly welcome those who are interested to pursue PhD and Master in Universiti Teknologi PETRONAS. We are seeking hardworking and committed individuals for the following research topics/areas:
[TAKEN] PROJECT 1: Development of clinical diagnostic and decision support tool for early knee osteoarthritis using non-invasive and in-vivo multinuclear magnetic resonance imaging
Osteoarthritis (OA) is the most common type of joint disease that will lead to failure of synovial joint organ and disability. Generally, OA affects the joint of spine, fingers, hips, knees and toe but it is most common in knee. It is known that knee OA is due to the gradual loss of articular cartilage (AC). The worldwide prevalence estimate for symptomatic OA is 9.6 % among men and 18 % among women. Disability due to OA has a huge negative impact to the economy (loss of productivity, health costs) of any country. …
Electrical & Electronic Engineering at UNIVERSITI TEKNOLOGI PETRONAS
SEND YOUR RESUME NOW!
Supervisor: Prof Fabrice MERIAUDEAU
Email : firstname.lastname@example.org
Deep Learning Techniques for Automatic Detection of DME or DR on OCT Images
Eye diseases such as Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are the most common causes of irreversible vision loss in individuals with diabetes. Just in United States alone, health care and associated costs related to eye diseases are estimated at almost $500 M  with prevalent cases of DR expected to grow exponentially affecting over 300 M people worldwide by 2025 . Early detection and treatment of DR and DME play a major role to prevent adverse effects such as blindness. DME is characterized as an increase in retinal thickness within one disk diameter of the fovea center with or without hard exudates and sometimes associated with cysts. Spectral Domain OCT (SD-OCT), which images the depth of the retina with a high resolution and fast image acquisition is an adequate tool, compared to fundus images for DME identification. However, very few works, up to our knowledge, have addressed the specific problem of DME and its associated features detection from OCT images.
Srinivasan et al.  proposed a classification method…