Medical Imaging

n. a.

The teaching methodologies provide the acquisition of theoretical concepts, the resolution of examples applied to biomedical imaging and the development of projects applied to real cases. 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 ofthe proposed exercises. In the research component students choose one of the proposed themes, and draw up a presentation for colleagues, giving rise to exchange of opinions on the subject. At the end of the semester the students develop a project that allows the consolidation of theoretical and practical knowledge

Familiarization with processing and analysis of digital images and its major areas of application. Acquire the concepts, techniques and main processing methods and image analysis for understanding, identifying andformulating strategies for solving problems that arise in the area of medical imaging.
Explore visualization and manipulation software for medical imaging. Know the advantages and risks of Diagnostic Computer Aided Systems.Develop habits of self­learning, of work in group and of oral communication.

I – Introduction to Digital Image Processing

 – Digital Image Processing

 – Main Application Areas

 – Overview of Digital Image Processing

 – Components of a Digital Image Processing System

II – Digital Image Fundamentals

 – Image formation processes

 – The human vision system

 – The medical image

 – Image Sampling and Quantization

 – Image Quality

 – Relationships between pixels and distance measurements

III – Image Processing in the Spatial Domain

– Gray Level transformations: Negative, Log, Gamma and piecewise-linear transforms

– Histogram processing: equalization, local histogram processing, image enhancement

– Enhancement Using Arithmetic and Logical Operations

 – Filtering in the spatial domain. Different types of filters

 – Image restoration

 – Applications

 IV – Frequency Domain Image Processing

 – Introduction to the Fourier Transform and the Frequency Domain

 – Filtering in the frequency domain. Different types of filters

 – Applications

V – Image Analysis, Representation and Description

 – Morphological image processing

 – Segmentation: Detection of Discontinuities, Thresholding, Region-Based methods

 – Shape and Texture Processing

VI – Medical Image Visualization and Manipulation Software

VII – Diagnosis Support Systems Based on Image Analysis

NAO

Dougherty, G. (2009). Digital Image Processing for Medical Applications, Cambridge Univ. Press. Cota ISEC: 1A-1-257 

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

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