Module Directory

Microscopy is now a cornerstone of cell, clinical, molecular, neuro- and developmental biology. This module provides an overlook of imaging in biomedical sciences, then focusses on modern applications of fluorescence microscopy.

The aim of this module is:

• To develop broad understanding of the field of bioimaging and its applications together with introducing technical skills in bioimaging.

By the end of this module, students will be expected to be able to:

1. Describe know the technical details and applications of the wide range of techniques used in biological and biomedical imaging, from ultrasound and MRI to photography and confocal microscopy.


2. Explain the basic principles of imaging and image formation in different imaging modalities.


3. Discuss examples of image-based, quantified solutions to biomedical (and/or clinical and/or industrial) problems.


4. Demonstrate practical knowledge of the analytical tools and statistical methods used to quantify image datasets.


5. Confidently and succinctly present an image-based problem and their proposed (or performed) analysis.

Imaging in biological and biomedical research and clinical settings is hugely important. In particular, there has been a dramatic development of microscopic methods for visualization of biological structures and physiological events.

Case studies from experts in the imaging field are presented. A special emphasis is on computational image quantification. A practical in digital image processing is held. Using datasets provided in the course, as well as their own (photographic) data, students learn to process images using freely available open-source software.

At the end of the course, each student presents a short 'elevator pitch' talk showing an imaging-based problem, then presenting a solution for its quantification.

Effective verbal communication and writing are transferable skills developed in this course.

Syllabus

• Introduction and outline.


• A brief history of imaging.


• Principles of imaging with regards to multiple modalities (clinical, non-microscopic imaging included (e.g. MRI, CT…).


• Eye vs. camera.


• Sensitivity of sensors, optical illusions.


• Patterns and gradients - art and science? – e.g. pathohistology as pattern recognition ('art') vs. slow gradients invisible to the eye.


• The need for digital quantification. Advances in machine vision & medical imaging.


• Basic optics. Perspex model – demonstration. Dimensions,contrast, wavelength.


• Noise and resolution.


• Dynamic range.


• Basics in computational image processing and quantification (2 lectures): Counting, segmentation, tracking. Combining different classifiers.


• Practical in computational image processing using (where possible) students' own data.


• Science communication using imaging. How are images used in publications? Requirements for a good micrograph figure. How are images used in a public context? Convincingly communicating results visually and through graphs.


• Imaging ethics – image manipulation in scientific research and public context. Guidelines in journals.


• Case study I – temperature-dependent cytoskeleton dynamics in fission yeast.


• Case study II – biofilm formation on voice prosthetics.


• Presentations (and marking) of students' image-based problem and solution.

This module will be delivered via:

• Lectures (13 hours).
• Two 1-hour specialist seminars.
• One 3-hour practical.
• Presentation.

The course content consists of taught lectures on bioimaging, elementary and advanced aspects of bioimaging techniques and applications, specialist lectures for case studies, and final presentation.