Year 1 Taught Modules
Please note that the details of modules can change year-to-year, depending on the availability of specific members of staff, but the list here shows the typical module programme.
|Cells and Systems
Fundamental concepts in molecular and cellular biology and genetics, and in the structural and functional aspects of biological systems. An introduction to human anatomy is also given.
|Programming and Software Carpentry
A re-introduction to the principles of programming as well as a crash course in how to code productively when using it for research. The immediate aim is preparation for other modules where good coding skills will allow for fast progress. For ONBI the focus is on learning and using the Python language in scientific computing and to control a Raspberry Pi that will then be used in the Light Microscopy practical work
|Scientific Computing using MATLAB
Introduction to MATLAB, and to the fundamental mathematics of imaging techniques. Worked examples will be coded in MATLAB.
|Introductory and Advanced Light Microscopy
Davis, Eggeling, Parton, Dobbie, O'Shea
The overall goal of the microscopy training is for the students to gain an advanced theoretical and practical understanding of how bright field and fluorescence microscopes are built, adjusted and used. This first week introduces the core principles of bright field and fluorescence microscopy with a mixture of theory and hands-on practical use of microscopes and demonstrations, including time spent in laboratories across the university
|Introductory and Advanced Medical Imaging Modalities
The principles of medical imaging modalities, including magnetic resonance imaging, positron emission tomography, computed tomography, and ultrasound. The principles of magneto-encephalography will also be introduced.
|Introductory and Advanced Image Analysis
Chappell, Grau, Jenkinson, Rittscher, Waithe
Principles of image analysis, including feature segmentation, statisical analysis, noise and artifact cleanup, and within-modality and across-modality image registration. Advanced image analyis methods will cover non-linear registration methods, distortion correction, and Bayesian analysis of image data.
The fundamental methods required to conduct statistical analysis of imaging data will be taught in this 1-week module. This will include hypothesis testing, Bayesian inference, statistical modelling, model selection, Markov chains, and hidden Markov models.
|Imaging Biomarker and Probe Design
Gouverneur, Tyler, Faulkner
Introduction to the use of biomarkers and probes in imaging. The use of F-18 PET agents will be covered, along with novel optical fluorescence markers and ultrasound agents. Smart MRI agents will be discussed, along with new hyperpolarized liquid state and gas phase agents.
|High Performance Computing
How large data sets are curated and managed, and how information is extracted from Big Data. Examples from large-scale imaging studies such as the Human Connectome Project and the UK Biobank Imaging Extension.
Academics and industry colleagues provide an overview of rotation projects that can be offered. Students may also set up meetings to discuss further details about the projects.
The basics of C++ are introduced as part of this 1-week module, with an emphasis on practical learning.
|Study Design, Clinical Trials and Research Governance
Jezzard, GSK, CTRG
Part of this module is provided by GSK, covering the ethics of animal and human research and an overview of how industrial clinical trials using imaging are conducted. Good Clinical Practice (GCP) training will also be provided by the Clinical Trials and Research Governance office.