Computer Vision in Medical Imaging
The research group in which the fellow will be integrated has extensive experience in the development of methodologies for the analysis of retinal images. The work plan now proposed consists of the development of image analysis/computer vision methods for the extraction of biomarkers associated with the retinal vascular network, namely the tortuosity associated with the vessels that constitute this vascular network. The extracted biomarkers could later be used for the prognosis of rare diseases, namely Fabry disease.
Master´s student in Biomedical Engineering, Computer Engineering, Computer Science, or related
Minimum profile required
Average degree equal to or greater than 14; experience in computer vision and/or deep learning.
Experience in chest x-ray image analysis; Python and PyTorch/Keras experience; desire to carry out a master's thesis in the area.
Since 20 Jul 2022 to 02 Aug 2022
Cluster / Centre
Networked Intelligent Systems / Biomedical Engineering Research