Estudia

• CG1-Organize and evaluate the learning and the research activity themselves and develop strategies to improve them
• CB7-That students know how to apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader contexts related to their area of ??study
• CG2-Interact in a multicultural environment through knowledge of the national and European cultures, human rights and European realities
• CB8-That students are able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on social and ethical responsibilities linked to the application of their knowledge and judgments
• CB10-That students have the learning skills to allow them to continue studying in a way that will mostly be self-directed or autonomous
• CT1-Organize and evaluate the learning and the research activity themselves and develop strategies to improve them
• CT2-Interact in a multicultural environment through knowledge of the national and European cultures, human rights and European realities
• CG7-That students know how to apply the knowledge acquired and their ability to solve problems in new or unfamiliar environments within broader contexts related to their area of ??study
• CG8-That students are able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on social and ethical responsibilities linked to the application of their knowledge and judgments
• CG10-That students have the learning skills to allow them to continue studying in a way that will mostly be self-directed or autonomous
• CE1-Ability to evaluate a detection algorithm and critical capacity to decide its daily clinical use. Estimate the crucial factors for its proper implementation
• CE2-Learn which algorithm(s) could be more suitable in a particular application
• CE35-Understand image registration and the similarity between images
• CE36-Analyze the current literature of registration algorithms used in medical image analysis, from the point of view of the computer vision enginer
• CE37-Ability to evaluate a detection algorithm and critical capacity to decide its daily clinical use. Estimate the crucial factors for its proper implementation
• CE38-Learn which algorithm(s) could be more suitable in a particular application

• Acquire a good knowledge on image similarity and similarity indexes
• Acquire a good knowledge on image registration: basic algorithms and task-specific algorithms, at both theoretical and practical levels.
• Understand, develop and implement different image registration algorithms on the topics of medical imaging using both 2D and 3D images.
• Be able to quantitatively evaluate algorithms providing clinically and medically relevant measures such as TLE/TRE.
• Obtain a good knowledge of existing software and libraries for the development of registration algorithms.

1. Introduction to Medical Image Registration and Applications

2. Intensity Image Registration. Overview

3. Non-rigid image registration

4. Feature based registration and matching

5. Current trends on medical image registration and fusion

• Goshtasby, Ardeshir (2012). Image registration : principles, tools and methods. Springer.
• Modersitzki, Jan (2004). Numerical methods for image registration. Oxford University Pres.
• Medical image registration (2001). CRC press.
• Insight into images : principles and practice for segmentation, registration, an (2004). Wellesley : A K Peters.
• Transactions on Medical Imaging . IEEE.
• Medical Image Analysis. Elsevier.

Assessment activities:

The evaluation is based on three different activities: 30% from Labs + 40% from the challenge + 30% exam.

Specific criteria for the "No show" grade:
If the student submits some of the activities, he will have a final mark. You will obtain a "no presentat" only if you dont' submit any activity for evaluation.

Single Assessment:
The student can undertake avaluació única ("Single evaluation"), by means of a single exam that will take into account the contents of all competences that should be acquired in the module.

Minimum requirements to pass:
Per considerar superada l’assignatura, caldrà obtenir una qualificació mínima de 5.0

To pass the module, a minimum mark of 5 over 10 is needed.

To stablish the appointments students can use moodle or sent emails to the teachers. These appointments can be done online via Teams meetings or in presence (Teacher offices)

The communitation and interaction with the student will be mainly done via moodle, having also specific forums for all the activities.

Students can also interact with the teacher via email or via videoconferences (google meet).