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Biomedical Imaging Analysis

Code: EBE0056     Acronym: AIBI

Keywords
Classification Keyword
OFICIAL Biomedical Engineering

Instance: 2016/2017 - 2S Ícone do Moodle

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

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
MIB 50 Syllabus 3 - 6 56 162

Teaching Staff - Responsibilities

Teacher Responsibility
Ana Maria Rodrigues de Sousa Faria de Mendonça

Teaching - Hours

Recitations: 3,00
Laboratory Practice: 1,00
Type Teacher Classes Hour
Recitations Totals 1 3,00
Ana Maria Rodrigues de Sousa Faria de Mendonça 3,00
Laboratory Practice Totals 2 2,00
Guilherme Moreira Aresta 1,00
Teresa Manuel Sá Finisterra Araújo 1,00
Mais informaçõesLast updated on 2017-02-03.

Fields changed: Examinations or Special Assignments, Melhoria de classificação, Componentes de Avaliação e Ocupação, Programa, Obtenção de frequência

Teaching language

Suitable for English-speaking students

Objectives










Main objectives are to develop knowledge and skills in: . concepts and methodologies for digital image processing; . principles, concepts and methods of physics and imaging technologies used in Biology and Medicine; . students' exposure to various forms of Image Analysis and Processing in Biology and Medicine (IAP-BM). Learning outcomes are: . knowledge acquisition in IPA-BM; . analysis of problems in IPA-BM; . design of IPA-BM; . oral and written presentation.


Learning outcomes and competences

Learning outcomes are: . knowledge acquisition in IPA-BM; . analysis of problems in IPA-BM; . design of IPA-BM; . oral and written presentation.

Working method

Presencial

Program

1. INTRODUCTION 1.1. The image processing cycle 1.2. The machine and computer vision cycle 1.3. The Biomedical image analysis cycle 1.4. Applications.

2. DIGITAL IMAGES: ACQUISITION, SAMPLING, QUANTIZATION AND REPRESENTATION 2.1. Introduction 2.2. Digital Images 2.3. Biomedical Images

3. IMAGE ENHANCEMENT 3.1. Basic intensity operations 3.2. Image enhancement using local operators 3.3. Methods in the frequency domain 3.4 Mathematical morphology in image enhancement.

4. FEATURE DETECTION 4.1. Introduction 4.2. Edge detection 4.3. Corner detectors 4.4. Blob detectors 4.5 Line and curve fitting .

5. IMAGE SEGMENTATION 5.1. Introduction 5.2. Feature domain 5.3. Image domain

6. QUANTITATIVE IMAGE ANALYSIS 7.1. Introduction 7.2. Connected components labeling 7.3. Feature measurement 7.4. Object representation.

7. APPLICATIONS in MEDICINE AND BIOLOGY

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

Teaching methods and learning activities

Lectures (classes TP) 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 lectures.

 

 

 

 

 

 

 

 

 

 

 

 

 

 







 

Software

Matlab 6 R12.1

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 60,00
Participação presencial 0,00
Trabalho laboratorial 40,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Estudo autónomo 74,00
Frequência das aulas 68,00
Trabalho laboratorial 20,00
Total: 162,00

Eligibility for exams

Type of evaluation: Distributed evaluation with final exam To be admitted to the final exam, the student: 1. Should not miss more than 25% of classes ( both TP and lab) (necessary condition); 2. Do a group assignment (study-EST) on a theme to be defined. The frequency grade (CF) is the grade of the group assignment. The final grade (NF) is calculated according to the following expression:NF = 0.6* PE +0.4 * F, where PE is the grade of the written final exam and F = min (CF, PE +4).

Calculation formula of final grade

The frequency grade (CF) is the grade of the group assignment. The final grade (NF) is calculated according to the following expression:NF = 0.6*PE+0.4*F, where PE is the grade of the written final exam and F = min (CF, PE+4).

Examinations or Special Assignments

1. Group assignment (40%)

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 grade will also be used for calculating the final grade in case of grade improvement exam.

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