The Course is divided into two parts: the first one  is dedicated to Biomedical Signal Analysis. The objective is to introduce the most diffused methods of information processing from biomedical signals and to describe the most significant applications in Medicine and Biology, in both physiological studies and in clinical applications for diagnosis, therapy and rehabilitation.
The second part of the Course  deals with Medical Images. The objective is to provide basic concepts for their characterization, to illustrate clinical and diagnostic problems and to introduce the principles on which some techniques for their processing and reconstruction are based.
The Course is constituted by frontal lessons, exercise sessions, seminars and laboratory exercise aiming at more deeply analyzing the topics of signal and image processing making use of MatLab. The attendance of the Course is strongly adviced.
Part  Medical Images, Prof Maria Gabriella Signorini
Provide basic concepts on biomedical images introduce the related clinical and diagnostic problems and illustrate principles on which techniques for processing and reconstruction are based on.
The Course is constituted by frontal lessons, exercise sessions and laboratory exercise The attendance of the Course is strongly recommended both at frontal lessons and exercise sessions whose content is also part of the evaluation procedure.
Programme of lessons and exercises
Medical Imaging modalities
Introduction to image classification. Image formation: Point Spread Function, Modulation Transfer Function, Spatial and amplitude resolution, Contrast, Signal to Noise ratio. Fourier Transform in the 2D spatial domain. Fotonic images. Artifacts and their removal. Human perception and Biomedical Images. Psychophysics Weber's Law. Perception thresholds for human vision.
Basic Principles for image processing and reconstruction
Sampling and quantization in the spatial domain. Discrete Fourier Transform in the 2D space domain. Convolution 2D. Image quality enhancement: spatial filters, equalization. Geometric operators. Tomographic reconstruction. Numeric approach to tomographic reconstruction: Radon transform, Sinogram, back-projection and blurring. Filtered back- projection. Ramp high pass filter, Central Slice Theorem.
X ray Imaging: basic radiography, X-ray generation, radiation interaction with matter, dose. X-ray instrumentation. Digital Radiology. Mammography, Angiographic X-Ray imaging. Computed Tomography (CT): applications, history and evolution of instrumentation, spiral CT.
Tomographic reconstruction application to CT images.
Nuclear medicine Imaging – Radioactivity. Nuclear Emission images. General principles Emission Tomography (SPECT). Detectors and data acquisition system. Positron emission Tomography (PET). Spatial resolution. Detectors. Instrumentation. Dual mode PET-CT scanners.
Magnetic Resonance Imaging (MRI): Principles, Instrumentation, Pulse Sequences, T1 and T2 contrast, image generation. FMRI.
The Course do not request mandatory prerequisites; it is advisable to be aware of the fundamentals of digital signal processing.
Valli G., Coppini G., Bioimmagini, Editore: Pàtron, Bologna, Terza Edizione, Anno edizione: 2012
Lesson Notes and other Course materials available for download at : https://beep.metid.polimi.it/
Webb Andrew, Introduction to Biomedical Imaging, Editore: IEEE Press - Wiley Interscience, 2004
The Course site collects didactic material supporting theoretical and practical lessons. The material is available for download before the course starts.