Biosignals and Biomedical Image Processing

Course guarantor:

Lecturer:

Tutor:

Supervisor:

Department of Software Engineering

Synopsis:

The aim of the course is to provide students with theoretical principles, techniques, and applications related to the processing and analysis of biological signals and medical images. During the course, students will work in MATLAB exercises on examples involving the processing of various biosignals. After completing the course, students should be able to design and implement solutions to complex tasks for biosignals and biomedical images, interpret the results, and apply their knowledge to real medical challenges.

Requirements:

Syllabus of lectures:

1. Introduction to biosignals, analogue to digital signal conversion

2. Time domain analysis of 1-D biosignals, discrete 1-D convolution and properties of convolution, correlation and autocorrelation of signals

3. Analysis of 1-D biosignals in the frequency domain, Discrete Fourier transform

4. Discrete Cosine Transform and Wavelet Transform and its Applications

5. 1-D biosignal filtering

6. Practical examples of processing ECG (electrocardiogram), EEG (electroencephalogram) and acoustic biosignals

7. 1-D biosignal processing using deep neural networks

8. Introduction to medical image data processing in radiology: x-ray, MRI (magnetic resonance imaging), CT (computed tomography) and ultrasound

9. Spectral analysis of 2-D and 3-D images and noise analysis in biological image data

10. (2) Medical image data processing, image registration, segmentation and classification techniques

11. Deep neural networks in medical image processing

12. Digital pathology and future trends in biosignal and medical image data processing

Syllabus of tutorials:

Study Objective:

The aim of the course is to provide students with theoretical principles, techniques, and applications related to the processing and analysis of biological signals and medical images. During the course, students will work in MATLAB exercises on examples involving the processing of various biosignals. After completing the course, students should be able to design and implement solutions to complex tasks for biosignals and biomedical images, interpret the results, and apply their knowledge to real medical challenges.

Study materials:

1. Rangayyan, Rangaraj M., and Sridhar Krishnan: Biomedical signal analysis. John Wiley & Sons, 2024. ISBN 978-1119825852.

2. John L. Semmlow, Benjamin Griffel: Biosignal and Medical Image Processing. CRC Press, 2014. ISBN 978-1466567368.

Note:

Further information:

courses

No time-table has been prepared for this course

The course is a part of the following study plans:

• Master specialization Visual computing and Game design (compulsory elective course)