Why study MSc(Eng) Bioengineering: 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 you 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 your final project, you will be exposed to the unmet clinical needs in biology and medicine and will be introduced in interdisciplinary research.
What you'll do
The MSc in Bioengineering: Imaging and Sensing is offered on a full-time basis over two years, starting in September. It requires completion of nine modules and a major research project dissertation.
You will be allocated an academic supervisor who will provide advice and guidance throughout the period of study.
The MSc(Eng) consists of:
- 3 compulsory modules (60 credits)
- optional modules (choose 6, totalling 80-110 credits)
- a major research project
Find out what current student Sai Ganesh has to say about studying this MSc - www.sheffield.ac.uk/eee/news/mscbioengineering-1.773050
Interdisciplinary Seminars in Biomedical Imaging & Sensing
This interdisciplinary seminar series will provide you with exposure and insight into unmet needs in medicine and biology with emphasis on those related to principles of state-of-the-art imaging and sensing techniques, their limitations, and emerging trends. You will interact with non-engineering experts from across medicine and life sciences, and there will be opportunities to observe some of these techniques first hand through site visits to clinical or biomedical research facilities within Sheffield.
Mathematics of Imaging Sciences
This module provides a set of mathematical tools necessary to understand, analyse, and implement modern image processing algorithms commonly used in practical medical imaging tasks.
Scientific Software Development for Biomedical Imaging
This module will provide you with the range of skills that are required to create effective, reliable, fast software code (C++/Python) for numerically intensive biomedical imaging research, and deploy these research code on research computing infrastructures, including desktop GPU, super-computing and cloud computing infrastructures.
Advanced Signal Processing
Physics of Light Microscopy of Cells and Tissues
Physics of Medical Imaging with Ionising Radiation
Physical Principles of Imaging: Radiation-Matter Interaction
Medical Image Computing
Bioimaging with Light and Sound
Interdisciplinary Optional Modules
The program allows for a exploring some additional elective modules from interdisciplinary domains that relate to imaging and image computing or their applications. More specifically, selected courses on anatomy, physiology, cell biology, physics of the senses, and vision and neurosciences, among others.
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.)
Is this course right for you?
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 from a good UK university or an equivalent international degree qualification.
If you have a 2:2 or equivalent, or industrial experience, we'll give your application individual consideration.
Students must have an overall IELTS grade of 6.5 with a minimum of 6.0 in each component, or equivalent.
If you have any questions about the course, please contact Dr Nathan Porter, MSc Admissions and Course Support Assistant.
Follow the link to find out what current students studying this course have to say www.sheffield.ac.uk/eee/news/mscbioengineering-1.773050
The Department has large industrial contracts with several industries. The skills you will gain will be of use for a range of employers as well as providing an ideal background for PhD research.
Our graduates could expect to work across the globe in a variety of roles including:
Employers in this field include Philips Healthcare, Siemens Healthcare, GE Healthcare, Toshiba Medical, AGFA, Microsoft Research, Hitachi Medical Systems and a wide range of SMEs working on bioengineering, biomedical technologies and specialised software development.
This degree is new and is yet to be accredited. The department will be seeking accreditation once a cohort of students graduates from the programme. When accreditation is obtained, it will be applied retrospectively to all students who have graduated from the programme.