Processamento e Análise de Imagem Médica

The teaching methodologies used provide the acquisition of fundamental theoretical concepts and their application to biomedical images. In lectures the teaching methodology is mainly expositive, complemented by the resolution and analysis of exercises. The laboratory classes allow the consolidation of theoretical knowledge through guided resolution and analysis of the results of the proposed exercises. At the end of the semester the students develop a project that allows the consolidation of theoretical and practical knowledge.
Evaluation: Exam (15 values) +Project (5 values)

Familiarization with digital biomedical images and its major areas of application. Acquire the concepts, techniques and main processing and analysis image methods that allow identifying and formulating strategies for solving problems that arise in the area of biomedical imaging. Explore visualization and manipulation software for medical imaging. Know the advantages and limitations of Diagnostic Computer Aided Systems.
Develop self-learning habits, ability to work in groups and oral communication.

1. Introduction to Digital Image Processing
1.1. What is Digital Image Processing?
1.2. Main Application Areas
1.3. Overview of Digital Image Processing
1.4. Fundamental Steps in Digital Image Processing
2. Digital Image Fundamentals
2.1. Visual perception
2.2. Light and the electromagnetic spectrum
2.3. Image acquisition
2.4. Image Sampling and Quantization
2.5. Image quality
3. Image Enhancement in the Spatial Domain
3.1. Gray Level transformations
3.2. Histogram processing
3.3. Enhancement using arithmetic and logical operations
3.4. Filtering in the spatial domain. Types of filters and their applications
3.5. Image restoration
4. Image Enhancement in the Frequency Domain
4.1. Introduction to the Fourier Transform and the frequency domain
4.2. Filtering in the frequency domain. Different types of filters
5. Image Analysis, Representation and Description
5.1. Morphological image processing
5.2. Segmentation: detection of discontinuities, edge linking and boundary detection, thresholding, region-based methods
5.3. Shape and texture processing
6. Medical Image Visualization and Manipulation Software
7. Computer Aided Diagnostic Systems

NAO

 Gonzalez, R. C., R., Woods E. (2008). Digital image processing, Pearson/Prentice Hall, 3rd Ed. Cota ISEC: 1A-11-31
 Woods, R. E., Eddins, S. L., & Gonzalez, R. C. (2009). Digital image processing using MATLAB. Cota ISEC: 1A-11-43
 Dougherty, G. (2009). Digital Image Processing for Medical Applications, Cambridge Univ. Press. Cota ISEC: 1A-1-257
 Demirkaya, O., Asyali, M. H., & Sahoo, P. K. (2008). Image processing with MATLAB: applications in medicine and biology. CRC Press. Cota ISEC: 12-2-5
 Silva, C., & Ribeiro, B. (2018). Aprendizagem Computacional em Engenharia. Imprensa da Universidade de Coimbra/Coimbra University Press. Cota ISEC: 1A-4-198
 Najarian, K., Splinter, R. (2006). Biomedical Signal and Image Processing, CRC Press, 2006. Cota ISEC: 12-2-4
 Dhawan, A. P. (2003). Medical Image Analysis, Wiley-IEEE Press. Cota ISEC: 12-2-3