BS333-6-AU-CO:
Bioimaging

The details
2019/20
Life Sciences (School of)
Colchester Campus
Autumn
Undergraduate: Level 6
Current
Thursday 03 October 2019
Saturday 14 December 2019
15
09 September 2019

 

Requisites for this module
BS225 or BS238
(none)
(none)
BS312, BS327

 

BS312, BS327

Key module for

(none)

Module description

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.

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

Module aims

This module aims to develop broad understanding of the field of bioimaging and its applications together with introducing technical skills in bioimaging.

Module learning outcomes

In order to pass this module, the student will need 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.

Module information

Syllabus:
1) Introduction and outline
2) A brief history of imaging
3) Principles of imaging with regards to multiple modalities (clinical, non-microscopic imaging included (e.g. MRI, CT…).
4) Eye vs. camera. Sensitivity of sensors, optical illusions.
5) Patterns and gradients - art and science? – e.g. pathohistology as pattern recognition ('art') vs. slow gradients invisible to the eye.
6) The need for digital quantification. Advances in machine vision & medical imaging.
7) Basic optics. Perspex model – demonstration. Dimensions,contrast, wavelength.
8) Noise and resolution
9) Dynamic range
10) Basics in computational image processing and quantification (2 lectures): Counting, segmentation, tracking. Combining different classifiers.
11) Practical (3h) in computational image processing using (where possible) students' own data
12) 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.
13) Imaging ethics – image manipulation in scientific research and public context. Guidelines in journals.
14) Case study I – temperature-dependent cytoskeleton dynamics in fission yeast (Dr Dan Mulvihill, University of Kent).
15) Case study II – biofilm formation on voice prosthetics (Dr Campbell Gourlay, University of Kent).
16) Presentations (and marking) of students' image-based problem and solution.

Learning and teaching methods

Lectures - 13 hrs Specialist seminars - 2 x 1 = 2 hrs Practical - 3 hrs 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.

Bibliography

  • Lee, M. (2019) 'Photography.', in Salem Press Encyclopedia of Science.
  • Fallon, L. Fleming, Jr., PhD. (2018) 'Microscopy.', in Magill’s Medical Guide (Online edition).
  • (no date) Seeing the Scientific Image - John Russ.
  • Oweida, Ayman, B.Sc., M.Sc. (2018) 'Radiology and Medical Imaging.', in Salem Press Encyclopedia of.
  • (no date) Nature milestones - Light Microscopy.
  • Schuler, Romana Karla. (2015) Seeing Motion: a History of Visual Perception in Art and Science, De Gruyter: De Gruyter.
  • Penno, Ellen E. Anderson, BS, MS, MD, FRCSC, Dip. ABO. (2018) 'Optics.', in Salem Press Encyclopedia of Science.
  • Tango, Gerardo G. (2018) 'Image Processing.', in Salem Press Encyclopedia of Science.
  • Milestones timeline : Nature Milestones in Light Microscopy, https://www.nature.com/milestones/milelight/timeline.html

The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework Online Assessment
Coursework Online Assessment
Coursework Online Assessment
Coursework Online Assessment
Coursework Digital Image online exercise
Coursework Oral Presentation

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Philippe Laissue, Dr Ben Skinner

 

Availability
No
No
No

External examiner

No external examiner information available for this module.
Resources
Available via Moodle
Of 24 hours, 12 (50%) hours available to students:
12 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information
Life Sciences (School of)

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