- Introduction to bioengineering - Systems and signals

The course provides basic knowledge on digital image processing focused on medical image data. After completion of the course the student will understand concepts as sampling, quantization, noise, interpolation or segmentation in the field of 2D or 3D imaging, and specifically for every medical image modality. Students will acquire skills to process digital images in the spatial and frequency domain, and will be able to use some advanced techniques as morphological processing or segmentation.

1. Basic introduction to medical image processing. Visual Perception. 2. Image Sampling and Quantization. 3. Interpolation and geometrical transformations. 4. Image enhancement in the spatial domain: Point processing 5. Color. Image file formats. 6. Image enhancement in the spatial domain: Filtering 7. Image enhancement in the frequency domain 8. Image compression 9. Medical Image segmentation, morphological processing and quantification. 10. Medical Imaging Modalities: conventional radiology, CT, Nuclear imaging, MR, US. 11. Advanced methods and Artificial Intelligence applications in medical imaging

Teaching methodology will be mainly based on lectures, seminars and practical sessions. Students are required to read assigned documentation before lectures and seminars. Lectures will be used by the teachers to stress and clarify some difficult or interesting points from the corresponding lesson, previously prepared by the student. Seminars will be mainly dedicated to interactive discussion with the students, present and evaluate homework. Grading will be based on continuous evaluation (including short-exams, homework, group essays, practical sessions, and student participation in class and Aula Global) and a final exam covering the whole subject. Help sessions and tutorial classes will be held prior to the final exam. Attendance to lectures, short-exams or submission of possible homework is not compulsory. However, failure to attend any exam or submit the exercises before the deadline will result in a grade of 0 in the corresponding exercise and will influence the final continuous evaluation score. The practical sessions may consist on laboratory work or visits to research or clinical centers. A laboratory report will be required for each of them. Homework exercises will also be a very important contribution, since they will imply solving a specific problem, proposing an algorithm and implement it using computer tools. The attendance to 80% of practical sessions is mandatory. Failure to hand in the laboratory reports on time or unjustified lack of attendance will result in 0 marking for that practice session.