Biomedical Imaging Analysis

Code:

L.BIO026

Acronym:

AIBI

Keywords
Classification	Keyword
OFICIAL	Biomedical Engineering

Instance: 2024/2025 - 2S

Active?	Yes
Web Page:	http://moodle.fe.up.pt
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Bachelor in Bioengineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L.BIO	36	Syllabus	3	-	6	52	162

Teaching language

Suitable for English-speaking students

Objectives

This is an introductory course on Image Processing and Analysis (IPA), where fundamental concepts and methods of these areas will be presented.

The learning objectives are essentially the development of knowledge and skills in:
. concepts and methodologies of digital image processing
. principles, concepts and methods of physics and imaging technologies used in Biology and Medicine (BM).

Learning outcomes and competences

Students who successfully complete this course should:
- understand and be able to explain the concepts of image processing and analysis and their fundamental algorithms;
- know and be able to select and apply these algorithms in practical situations;
- have acquired the knowledge to use a library that implements some of the algorithms studied;
- be able to analyze and understand selected scientific articles in the areas of image processing and analysis.
- be able to develop simple image analysis systems, according to the specifications defined, applying the most appropriate technological tools.

Working method

Presencial

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

Knowledge of MatLab.

Program

0. Presentation of the curricular unit.

1. Introduction: The Image Analysis/Computer Vision cycle. Applications.

2. Digital Images: Introduction. Acquisition and formation of digital images. Monochrome and polychrome images. Brief considerations on digital topology.

3. Image enhancement: Basic intensity transformations. Image enhancement using local linear and non-linear operators.

4. Image segmentation: Introduction. Feature-based segmentation. Image-based segmentation (regions and contours).

5. Feature detection: Introduction. Edge detection. Curve detection. Corner detection. Salient region detection. "Matching features and regions.

6. Quantitative analysis. Introduction. Region labeling. Measuring morphological, dimensional and topological characteristics.

7. Introduction to image recognition.

Mandatory literature

Gonzalez, Rafael C; Digital image processing using Matlab. ISBN: 0-13-008519-7
Gonzalez, Rafael C; Digital image processing. ISBN: 0-201-50803-6

Complementary Bibliography

Milan Sonka; Image processing, analysis and machine vision. ISBN: 978-0-495-24428-7

Teaching methods and learning activities

Lectures (classes TP) for exposing the main topics of the syllabus, always with illustrative examples.

Lab work (classes PL) with the development by the students of application problems of the concepts and methods taught in the theoretical lectures.

Software

MatLab

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	60,00
Trabalho prático ou de projeto	40,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	62,00
Frequência das aulas	52,00
Elaboração de projeto	40,00
Apresentação/discussão de um trabalho científico	2,00
Trabalho escrito	6,00
Total:	162,00

Eligibility for exams

Conditions for frequency:

1. Do not exceed the legal number of absences in the theoretical-practical and laboratory classes (necessary condition);
2. To develop a group assignment (project) on a topic to be defined; the assignment must be presented by the members of the group in a session to be held in the theoretical-practical classes.

Calculation formula of final grade

The frequency mark (CF) is the mark of the group assignment.

The final grade (NF) is calculated by NF=0.6*Ex+0.4*CF where Ex is the exam grade and CF is the frequency gmark.

Students can only pass the course if their exam mark , Ex, s equal to or higher than 8.00.

Examinations or Special Assignments

1. Group project;

2. Examination covering all course subjects.

Special assessment (TE, DA, ...)

Students with a special status will be evaluated as regular students.

Classification improvement

Students have to attend recurso (resit) exam to improve their grades. The exam will cover the entire program. The frequency mark will also be used for calculating the final grade in case of grade improvement exam.

The attendance grade can only be improved by attendance in the following year.