Image processing, programming, statistics. Advanced programing skills in Matlab are essential to follow the sessions, which will have a high practical content based on algorithm programing in Matlab.

The objective of this course is to allow the students to understand the main image reconstruction techniques used in the CT, PET, SPECT and MRI medical imaging systems, not only from a theoretical point of view, but also in a practical way through the implementation of the algorithms in Matlab. At the same time, the student will become familiar with the data acquired in each type of system, which is essential to be able to correctly approach the reconstruction problem.

This course covers the main image reconstruction techniques used in the tomographic imaging systems TAC, PET, SPECT and MRI. It will allow the student to get familiar with the acquired data in each system that enable the generation of the tomographic image, basic to be able to approach the reconstruction problem. The contents can be sumarized in (see more details in the weekly planning): 1. Introduction to tomographic image reconstruction. 2. Imaging basics: spatial resolution, noise/artefifact, Fourier transform, Radon transform. 3. Acquisition geometries: parallel beam, fan beam beam and cone beam. 4. Analytical algorithms. 5. Iterative algorithms. 6. Advanced methods. 5. Practical applications in different image modalities.

The course will be mostly in computer room to put in practice all the concepts.