Checking date: 01/07/2019


Course: 2019/2020

Medical Image Reconstruction
(18060)
Study: Master in Information Health Engineering (359)
EPI


Coordinating teacher: ABELLA GARCIA, MONICA

Department assigned to the subject: Department of Bioengineering and Aerospace Engineering

Type: Electives
ECTS Credits: 6.0 ECTS

Course:
Semester:




Students are expected to have completed
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.
Competences and skills that will be acquired and learning results.
CB6 Having and understanding the knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context CB7 Students know how to apply their acquired knowledge and problem-solving skills in new or unfamiliar settings within broader (or multidisciplinary) contexts related to their field of study. CB8 Students are able to integrate knowledge and to face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of their knowledge and judgments. CB9 Students know how to communicate their conclusions and the knowledge and ultimate reasons behind them to specialised and non-specialised audiences in a clear and unambiguous way. CB10 Students have the learning skills that will enable them to continue studying in a way that will be largely self-directed or autonomous. General competences CG2 Ability to apply the knowledge of skills and research methods related to engineering. CG3 Ability to apply the knowledge of research skills and methods related to Life Sciences. CG4 Ability to contribute to the widening of the frontiers of knowledge through an original research, part of which merits publication referenced at an international level. CG5 Ability to perform a critical analysis and an evaluation and synthesis of new and complex ideas. CG6 Ability to communicate with the academic and scientific community and with society in general about their fields of knowledge in the modes and languages commonly used in their international scientific community. Specific competences CE6 Ability to understand the basis of the main technologies involved in biomedical imaging systems. CE7 Ability to solve a biomedical problem from an engineering perspective based on the acquisition and processing of biomedical images
Description of contents: programme
1. Introduction to tomographic image reconstruction. Inverse problem. 2. Analytical algorithms. 3. Iterative algorithms. 4. Advanced methods. 5. Practical applications in different image modalities.
Learning activities and methodology
The course will be mostly in computer room to put in practice all the concepts.
Assessment System
  • % end-of-term-examination 70
  • % of continuous assessment (assigments, laboratory, practicals...) 30
Basic Bibliography
  • Aninash C. Kak, Malcolm Slaney. Principles of Computerized Tomographic Imaging (Classics in Applied Mathematics). Society for Industrial and Applied Mathematics. 1987
Additional Bibliography
  • Frank Natterer. The Mathematics of Computerized Tomography. SIAM. 2001
Recursos electrónicosElectronic Resources *
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The course syllabus and the academic weekly planning may change due academic events or other reasons.