Signal Processing and Imaging 390-FM2-1ASO
Profile of studies: general-academic
Form of study: full-time
Type of subject: obligatory (module "Mathematical and computer methods").
Field and discipline of science: field of exact and natural sciences, discipline of mathematical sciences.
Year of study / semester: year 1 / semester 2
Number of hours of classes: lecture 30 hours, laboratory 30 hours
Teaching methods: lecture, problem solving and tasks, discussion, consultations, self-study outside of the classroom
ECTS credits: 4
Balance of student workload: participation in lectures (30 hours), participation in the laboratory (30 hours), participation in consultations (15 hours), own work outside classes (30 hours), preparation for the exam 15 hours), total student workload (120 hours).
Quantitative indicators: student workload associated with activities requiring direct teacher participation - 3.6 ECTS; student workload related to practical activities - 1.2 ECTS.
The lecture and closely related laboratory activities cover the following issues:
1. Basic concepts in the field of signal processing and analysis. Sources, classification and parameters of signals.
2. Acquisition and processing of signals.
3. Analysis of signals in the field of time.
4. Frequency analysis of discrete signals and its interpretation.
5. Digital filtration. Algorithms of digital filtration.
6. Basic methods of digital signal analysis. Identification of audio signals.
7. Image: definition, structure and types.
8. Principles of creating a digital image. Methods of acquiring of digital images.
9. Color images, color models.
10. Non-context image processing (point, arithmetic and geometric).
11. Context image filtration (linear and nonlinear filters, two-dimensional discrete Fourier transform, spatial filtration).
12. Morphological transformations.
13. Analysis of digital images. Methods of image segmentation and indexing.
14. Measurements on digital images, including evaluation of object sizes and shapes, texture analysis, creation of statistics.
The lectures are enriched with presentations (use of Power Point software) with numerous examples of transmitted content. Students are stimulated to ask questions and discussions. Laboratory classes take place in the computer lab. During the course, basic algorithms for processing 1D and 2D signals are implemented. Students perform practical tasks in the field of signal analysis and imaging, indicated by the teacher, including applications in medicine. The teacher encourages students to teamwork.
Type of course
obligatory courses
Mode
Requirements
Prerequisites
Prerequisites (description)
Course coordinators
Learning outcomes
A student:
1. knows the physical and mathematical bases of contemporary methods of medical imaging, including X-ray and computer tomography as well as imaging using non-ionizing methods (K_W27)
2. knows mathematical tools for the analysis of experimental data, analysis of signals and images, including medical diagnostic images (K_W29)
3. knows methods of image creation, including digital image, knows methods of processing and improving the quality of images and signals (K_W30)
4. knows techniques of image analysis, optimization and recovery of quantitative information (K_W31)
5. knows the methods of images acquiring and diagnostic signals for medical applications (K_W32)
6. can use the literature, Internet resources and technical documentation of medical equipment - including documentation in English, knows the basic sources of information on current problems and achievements in medical physics (K_U40)
7. is aware of the continuous and rapid development of medical physics, can determine the direction of their interests and take of independent education (K_U41)
Assessment criteria
After completing the training, a written and oral exam is taken from the lecture.
The condition for admission to the lecture exam is to obtain a positive grade from passing the laboratory.
Bibliography
Recommended literature:
1. J. Szabatin, Podstawy teorii sygnałów, WKiŁ, Warszawa 2002.
2. S. Umbaugh, Digital image processing and analysis, CRC Press Taylor & Francis Group, 2011.
3. R. Tadeusiewicz, P. Kohoroda, Komputerowa analiza i przetwarzanie obrazów, Kraków 1997, WFPT. http://winntbg.bg.agh.edu.pl/skrypty2/0098/komputerowa_analiza.pdf
Additional literature:
1. T.P. Zieliński, Cyfrowe przetwarzanie sygnałów, WKiŁ, Warszawa 2005.
2. J. Cytowski, Cyfrowe przetwarzanie obrazów medycznych, Akademicka Oficyna Wydawnicza EXIT, Warszawa 2008.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: