k.m.rajpoot AT cs.bham.ac.uk
Programme Lead (Computer Science)
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medical image analysis, cardiovascular imaging, cardiac electrophysiology, computational pathology, machine learning
I am particularly interested in the development and application of computational algorithms and machine learning for understanding and analysing biomedical data, in particular medical images.
Functional neuroimaging data is openly available from multi-center studies for investigation of various cognitive and mental health issues. A promising stream of research in this domain is the utilization of machine learning algorithms to study brain connectivity & the affects due to cognitive processes or mental disorders. This project concerns the study of recent clustering and classification algorithms for mining functional neuroimaging data. You should have an interest (and/or skills) in machine learning, brain understanding, and scientific research to work in this area.
I am interested to explore deep learning (in particular, deep convolution neural network) for analysis of medical images. This study can be facilitated with deep learning libraries like Theano, TensorFlow, matconvnet. You should have an interest (and/or skills) in artificial intelligence, machine learning and scientific research to work in this area.
This project concerns the development of a graphical user interface and/or parallel processing routines for processing optical cardiac mapping data which concerns electrophysiological activity data of the heart. You should have interest (and/or skills) in software development and scientific research to work in this area.
In addition, I am interested to work in general in the following areas: medical image segmentation for quantitative analysis, medical image enhancement for improved analysis, and medical/health informatics. The BSc/MSc students are welcome to discuss own project ideas related to above areas.
Last updated: 9th March, 2018