Biosignals and Biomedical Image Processing
| Code | Completion | Credits | Range | Language |
|---|---|---|---|---|
| NI-BSO | Z,ZK | 5 | 2P+2C | Czech |
- Course guarantor:
- Vanda Benešová
- Lecturer:
- Vanda Benešová
- Tutor:
- Vanda Benešová
- 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 on examples of processing various biosignals in the MATLAB environment. After completing the course, students should be able to design and implement solutions to complex tasks for biosignals and biomedical images, interpret results, and apply their knowledge to real-world medical challenges.
- Requirements:
- Syllabus of lectures:
-
1. Introduction to biosignals, conversion of analog signals to digital.
2. Analysis of 1-D biosignals in the time domain, discrete 1-D convolution and convolution properties, 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 their applications.
5. Filtering of 1-D biosignals.
6. Practical examples of processing ECG (electrocardiogram), EEG (electroencephalogram), and acoustic biosignals.
7. Processing 1-D biosignals using deep neural networks.
8. Introduction to processing medical imaging data 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 imaging data.
10. Processing of medical imaging data, image registration, segmentation, and classification techniques.
11. Deep neural networks in medical image processing.
12. Digital pathology and future trends in the processing of biosignals and medical imaging data.
- Syllabus of tutorials:
-
1. Introduction to biosignals, conversion of analog signals to digital.
2. Analysis of 1-D biosignals in the time domain, discrete 1-D convolution and convolution properties, 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 their applications.
5. Filtering of 1-D biosignals.
6. Practical examples of processing ECG (electrocardiogram), EEG (electroencephalogram), and acoustic biosignals.
7. Processing 1-D biosignals using deep neural networks.
8. Introduction to processing medical imaging data 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 imaging data.
10. Processing of medical imaging data, image registration, segmentation, and classification techniques.
11. Deep neural networks in medical image processing.
12. Digital pathology and future trends in the processing of biosignals and medical imaging data.
- 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.
- Study materials:
-
Rangayyan, Rangaraj M., and Sridhar Krishnan: Biomedical signal analysis. John Wiley & Sons, 2024. ISBN 978-1119825852.
John L. Semmlow, Benjamin Griffel: Biosignal and Medical Image Processing. CRC Press, 2014. ISBN 978-1466567368.
- Note:
- Further information:
- https://courses.fit.cvut.cz/NI-BSO/
- Time-table for winter semester 2025/2026:
- Time-table is not available yet
- Time-table for summer semester 2025/2026:
- Time-table is not available yet
- The course is a part of the following study plans:
-
- Master specialization Computer Security, in Czech, 2020 (elective course)
- Master specialization Design and Programming of Embedded Systems, in Czech, 2020 (elective course)
- Master specialization Computer Systems and Networks, in Czech, 202 (elective course)
- Master specialization Management Informatics, in Czech, 2020 (elective course)
- Master specialization Software Engineering, in Czech, 2020 (elective course)
- Master specialization System Programming, in Czech, version from 2020 (elective course)
- Master specialization Web Engineering, in Czech, 2020 (elective course)
- Master specialization Knowledge Engineering, in Czech, 2020 (elective course)
- Master specialization Computer Science, in Czech, 2020 (elective course)
- Mgr. programme, for the phase of study without specialisation, ver. for 2020 and higher (elective course)
- Study plan for Ukrainian refugees (elective course)
- Master specialization System Programming, in Czech, version from 2023 (elective course)
- Master specialization Computer Science, in Czech, 2023 (elective course)