Biomedical image analysis

Code:

MVCOMP10

Acronym:

AIB

Keywords
Classification	Keyword
CNAEF	Engineering and related techniques

Instance: 2022/2023 - 2S

Active?	Yes
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Master in Computer Vision

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MVCOMP	11	Syllabus	1	-	6	42	162

Teaching language

English

Objectives

Knowledge of advanced techniques specific to biomedical image processing and analysis.

Analysis of current biomedical imaging applications, and ability to evaluate existing solutions, as well as the development of new specific solutions.

Evaluation of the adequacy of the methodologies applied in a multidisciplinary context for biomedical environments.

Ability to write documentation and scientific-technical results reports.

Learning outcomes and competences

Knowledge of advanced techniques specific to biomedical image processing and analysis.

Analysis of current biomedical imaging applications, and ability to evaluate existing solutions, as well as the development of new specific solutions.

Evaluation of the adequacy of the methodologies applied in a multidisciplinary context for biomedical environments.

Ability to write documentation and scientific-technical results reports.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Previous knowledge of signal and image processing.

Program

Advanced techniques of biomedical image processing and analysis.

Advanced techniques of segmentation in biomedical images.

Recognition of patterns in biomedical images.

Advanced brain imaging techniques.

Advanced applications of biomedical image analysis.

Mandatory literature

Editors: Wilson, David, Laxminarayan, Swamy; Handbook of Biomedical Image Analysis , 2005
Aly A. Farag; Biomedical Image Analysis, Statistical and Variational Methods, 2014
...; Artigos em conferências e revistas da área (ISBI, MICCAI, T-MI, IEEE Transactions on Biomedical Engineering, etc.)

Teaching methods and learning activities

Participatory lectures, laboratory practices and in computer rooms, conferences, learning based on the resolution of practical cases, use of the virtual classroom, autonomous work and independent study of students, group work and collaborative learning, preparation and presentation of work course. The annual teaching guide of the subject will include the details on the learning methodology. The evaluation will be supported in the projects (3) developed during the trimester.

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Participação presencial	10,00
Trabalho prático ou de projeto	90,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Apresentação/discussão de um trabalho científico	21,00
Elaboração de projeto	21,00
Total:	42,00

Eligibility for exams

Presence in class > 2/3
Submission of the majority of the mini-projects

Calculation formula of final grade

Nota = 0.9*NTrab + 0.1*Pres

NTrab = Average grade of mini-projects
Pres = presence and calss participation