Medical image analysis, machine/deep learning, lung cancer
CAD systems for automatic detection of pulmonary nodules on CT are one of the most studied applications. Although these systems improve the performance of radiologists, they usually only allow the visual description of tumours, limiting themselves to a subjective and qualitative characterization. The objective of LuCaS is to create a radiomics-based approach to describe and create of predictive models relating images' phenotypes with genomics' signatures, based on a non-invasive methodology.
PhD in bioengineering, electrical and computer engineering, computer sciences or similar
Minimum profile required
Experience in projects related to image processing and machine learning.
Experience in image processing and analysis, machine learning, Python, OpenCV, Matlab.
Since 28 Jan 2019 to 22 Feb 2019