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Medical Images Processing

Code:

LTB32002

Sigla:

PIM

Áreas Científicas
Classificação	Área Científica
OFICIAL	Electrotecnia

Ocorrência: 2021/2022 - 2S

Ativa?	Yes
Unidade Responsável:	Departamento de Engenharia Eletrotécnica
Curso/CE Responsável:

Ciclos de Estudo/Cursos

Sigla	Nº de Estudantes	Plano de Estudos	Anos Curriculares	Créditos UCN	Créditos ECTS	Horas de Contacto	Horas Totais
LTB	41	Plano de Estudos	3	-	3	45	81

Língua de trabalho

Portuguese

Objetivos

It aims to provide students of specific knowledge in areas that allow the analysis and the development of a digital medical image processing system. It introduces concepts and methods of digital image processing to enable the development of applications. Use appropriate tools to digital image processing, particularly the Matlab and specific toolbox. Identify and solve specific problems of medical imaging.

Resultados de aprendizagem e competências

- Know the various image formats and color spaces;

- Know some medical image acquisition equipment and the effect of resolution on the quality of these images;

- Know and develop image pre-processing algorithms;

- Know and develop algorithms for segmentation and feature extraction;

- Know how to develop an information extraction system based on image processing using the Matlab or GNU Octave simulation tool.

Modo de trabalho

Presencial

Programa

- The Human Visual System.
- Concept and representation of digital image.
- Steps of a digital image processing system.
- Acquisition of medical imaging.
- Sampling, quantization and resolution.
- Geometry of image formation.
- Histogram.
- Characterization of noise and its elimination.
- Morphological operations.
- Change in image contrast.
- Local and global detection of contours and lines
- Detection of the region of interest
- Feature extraction

Bibliografia Obrigatória

Gonzalez, R. e Woods, R.; Digital Image Processing
Semmlow, John L.; Biosignal and Biomedical Image Processing – Matlab-Based Applications

Bibliografia Complementar

Rangayan, R.; Biomedical Image Analysis
Ballard, Dana H. and Cristopher, M. Brown; Computer Vision

Métodos de ensino e atividades de aprendizagem

The pedagogic methodology used in this curriculum unit is based on two components: lecture method and work in laboratory environment. Will be used an e-learning platform (Moodle) to support teaching, as repository of information, forum and delivery of work. The evaluation of the discipline consists of laboratorial works using software Matlab or GNU Octave involving the digital image processing and a project.

Software

Matlab ou GNU Octave

Tipo de avaliação

Distributed evaluation without final exam

Componentes de Avaliação

Designation	Peso (%)
Trabalho laboratorial	100,00
Total:	100,00

Componentes de Ocupação

Designation	Tempo (Horas)
Estudo autónomo	36,00
Frequência das aulas	45,00
Total:	81,00

Obtenção de frequência

Laboratory and project work delivered and approved.

Fórmula de cálculo da classificação final

The final grade of the course is calculated as follows:

FG= 0,70 * LW + 0,30 * Pr

where
FG - Final Grade
LW - Laboratory work (note 1)
Pr - Project (note 2)

(1) The LW component consists of the average of the laboratory work grades. This component must have an evaluation equal to or greater than 9.50. This component is not assessed at exam time.
(2) The Pr component must have an evaluation equal to or greater than 9.50.