Objectives of Programme's Learning Outcomes

• Have acquired highly specialised and integrated knowledge and broad skills in the various disciplines of computer science, which come after those within the Bachelor's in computer science.
• Manage large-scale software development projects.
• Apply, mobilise, articulate and promote the knowledge and skills acquired in order to help lead and complete a project.
• Lead a project by mastering its complexity and taking into account the objectives, allocated resources and constraints that characterise it.
• Demonstrate independence and their ability to work alone or in teams.
• Manage research, development and innovation.
• Understand unprecedented problems in computer science and its applications.
• Organise and lead a research, development or innovation project to completion.
• Methodically research valid scientific information, lead a critical analysis, propose and argue potentially innovative solutions to targeted problems.
• Master communication techniques.
• Communicate, both orally and in writing, their findings, original proposals, knowledge and underlying principles, in a clear, structured and justified manner.
• Where possible, communicate in a foreign language.
• Apply scientific methodology.
• Critically reflect on the impact of IT in general, and on the contribution to projects.

Learning Outcomes of UE

develop an applied image and/or video processing system for medical applications, together with a critical analysis of the problem;
understand image representation taking into account the particularities and modalities of medical images and applied digital image analysis (low-level and high-level methods for denoising, segmentation,...) and processing methods, taking into account current usual tools in the field;
have direct contacts with actors in medical applications to have a better understanding of the applied field and constraints.

Content of UE

image processing (low-level processing, image understanding); medical image analysis (image acquisition, modalities & features);

Prior Experience

fundamentals of signal processing (sampling & quantization)

Type of Assessment for UE in Q2

• Oral Examination

Q2 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

• Oral examination

Q3 UE Assessment Comments

Not applicable