Biomedical Image Analysis with applications using AI/ML BIOL5443

  • Academic Session: 2024-25
  • School: MVLS College Services
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 2
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No

Short Description

This course will provide students with a broad foundation in the area of biomedical image analysis that will encompass both quantitative image analysis techniques along with the use of AI and machine learning. This course will train students in the fundamentals of image analysis techniques and how Deep Learning can be applied in various medical research areas, corresponding statistical analysis while also ensuring students consider the ethical consequences of the applications of such technology in research/clinical diagnostics.

Timetable

Teaching will take place over 5 weeks in semester 2 and will consist of lectures and tutorials of 1-2 hr(s) duration.

Requirements of Entry

None

Excluded Courses

None

Co-requisites

None

Assessment

50% - Written Essay (2000 words) (ILOs 1, 2 and 4)

50% - Oral Presentation on Image Analysis Task (presentation time, including Q & A, totalling 15 mins) (ILOs 3 and 4)

Course Aims

The aims of this course are to:

 

1. Provide students with an understanding of the primary concepts of imaging and image analysis techniques

2. Train students in the practical application of image analysis techniques through specific case studies or applications relevant to biomedical research

3. Provide students with an appreciation of the ethical concerns of appropriate use of image analysis techniques/software to ensure integrity of generated data

Intended Learning Outcomes of Course

By the end of this course students will be able to:

 

1. Critically discuss the differences between quantitative and AI/ML based image analyses techniques

2. Critically appraise the advantages and limitations of quantitative and AI/ML imaging techniques as applied in research/diagnostics.

3. Design and effectively implement appropriate image analysis workflows

4. Critically evaluate the ethical considerations of using these techniques 

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.