London: The University of Sheffield , UK has recently launched a new MSc in Biomedical Imaging and Sensing .
This exciting new, two year MSc programme is concerned with a wide range of biomedical imaging and sensing science and technology. Biomedical Imaging and Sensing is, in a broad sense, a set of competencies from engineering and sciences to support future quantitative biology and personalised medicine. It will provide students with theoretical and practical knowledge to develop methods and systems for disease understanding, diagnosis, prognosis and therapeutics where imaging and sensing play a key role.
The programme will cover:
the physics and physiology associated to data acquisition from biological tissue samples and human patients via a wide range of sensing/imaging modalities;
information processing methods to extract relevant signal and imaging features, which are relevant to biologists and clinicians;
aspects related to big data and predictive analytics, that is, extracting and analysing signals and images and developing machine learning methods from very large scale databases to support stratified medicine and systems biology.
The course is focused on the methods and systems and, hence, the foundations on engineering and science. However, through an interdisciplinary seminar series and final project, students will be exposed to the unmet clinical needs in biology and medicine and will be introduced in interdisciplinary research.
Major research project
Opportunities may exist for dissertation studies to be carried out in collaboration with other university research centres or with industrial organisations. Examples of research projects include:
Non-rigid image registration for computing cardiac motion from cine MRI
Extraction of vascular networks from digital subtraction angiography
Three-dimensional reconstruction of coronary trees from rotational angiography data
Detection and tracking of cells from time lapse microscopy images
Computing brain tissue tractography from diffusion MR imaging
Robust segmentation of medical images using statistical shape models
Computing atlases of the development bone and assessment of bone maturity
Autonomous pattern recognition and classification for biomedical imaging with possible applications to cancer, lung tomography (EIT, CT, MR etc.)
Eligibility – This course is designed for students with a 2:1 honours degree in an Engineering related subject, or from backgrounds including Physics, Mathematics and Computer Science or an equivalent international degree qualification (at above 60% pass rate) or or an approved professional qualification. Students must have an overall IELTS grade of 6.5 with a minimum of 6.0 in each component, or equivalent.