# Medical Sciences with Biomedical Engineering BSc (A144)

## Image Processing

### Module aims

In this module you will:

-be introduced to digital image processing relevant methods for image analysis.

-develop an appreciation of aspects of computation in interpreting or “parsing” images

-be introduced to some of the biomedical, clinical and research applications of image processing and computer vision.

### Learning outcomes

Upon successful completion of this module you will be able to:

• Describe the key concepts in image analysis including image types, representations & basic operations & transformations.
• Discuss common topics relevant to computer vision including potential applications of image processing and computer vision (medical & non-medical) and the relationships between mammalian visual systems and standard computational approaches to vision.
• Calculate linear image transforms numerically.
• Apply effectively moment calculations and the Hessian matrix to capture information about spatial structure.
• Apply effectively a range of neighbourhood image operators including spatial convolution using mask design where needed.
• Distinguish where image segmentation is necessary and describe image segmentation approaches and applications.
• Write code for quantitative image processing making use of common image processing tools in Matlab
• Systematically identify, label and quantify spatially localised structures using semi-automated methods

### Module syllabus

In this module you will cover the following topics:

1. Basic Concepts: introductory topics and biological vision

2. Binary Images and how these can be processed

3. Image Transforms

4. Neighbourhood Operators

5. Image Segmentation

6. Image Registration

7. Data Driven Approaches

### Pre-requisites

Calculus, derivatives, Linear Algebra. Eigenvalues and eigenvectors of a matrix. Knowledge of random variables would also be useful.

### Teaching methods

Lectures: 20 hours

Labs: 18 hours

### Assessments

Examinations:

●  Written exam:  80% weighting

Courseworks:

●  Quiz: 20% weighting;

1 quiz, which will be on the last week of instruction, during the lab session