• 054292 - BIOMEDICAL SIGNAL PROCESSING AND MEDICAL IMAGES [2] - BIOE 421

• Blended Learning & Flipped Classroom

Aim of the course is to enable students to master signal and image processing methods and to acquire capabilities to the application in the biomedical field.  Students will acquire theoretical notions and will be guided to the main application tools with exercise classes and personal work

The Course covers medical images and analysis from the theory to the practical applications.

 The Course is organized into two parts: the part [2] is dedicated to Medical images. 

The goal is providing basic concepts on biomedical images by introducing the related clinical and diagnostic problems.  Principles on which techniques for processing and reconstruction are based on are presented.

The Course is organized in frontal lessons (25 hours), practical exercise sessions with laboratory exercises (15 hours) aiming at deeply analyzing topics related to image processing by acquiring also practical knowledge making use of MatLab Tools.

5 hours will be spent in project development on topic of the Course proposed to students organized in groups with Tutor involvement and periodic revisions during the activity. 

0,5 CFU (5 hours) will be delivered through innovative teaching methods as “Blended Learning” and “Flipped Classroom”. Students will be actively involved studying and presenting to the class an assigned topic with the supervision of the laboratory tutors and teaching assistants with a final guided discussion.

Inside these activities 1 assignment will be proposed as autonomous student activity. The attendance to the Course is strongly advised both at frontal lessons and exercise sessions whose content is also part of the final evaluation.

The student will acquire methodological knowledge about Medical Images processing and analysis as well as applications and their main processing tools.

Students will be able to work on Medical Images with analysis and processing Matlab tools.

Moreover, through the knowledge of advanced methods and parameters measuring physiological system changes, they should be able to work autonomously in application problems different from those addressed in the lessons and/or in the practical exercises.

MEDICAL IMAGES

 Teaching Activity (25+5 hours)

• What a biomedical image is? Overview on the different techniques contributing to the generation of biomedical images. Present and future challenges and perspective.
• The concept of spatial resolution: from 1D to 2D definition of frequency. Point spread function and its relationship with contrast.
• 2D Fourier transform: pipeline of frequency analysis application to images. The properties of the transformation and their parallel to 1D Fourier transform.
• Analog to digital conversion: general workflow from acquisition to digitalization: the sampling theorem, the aliasing phenomenon, quantization error in images. Quantization and resolution trade-off.
• Numerical processing: point operators, intensity transformation. Definition of image histogram and contrast enhancement methods. 2D convolution, differential operators and edge detection kernels.
• Different types of noise corrupting biomedical images: gaussian, salt and pepper and methodologies for their removal.
• Ionizing radiations and radiodiagnosis with X rays: physical principles, X-ray machinery, production, and interaction with matter, detectors, and possible factors contributing to image degradation.
• Computerized tomography: the concept of projections, different models for CT scanners, and clinical applications
• Image reconstruction by projections: the tomographic plane, Radon transform and sinogram, back-projection, filtered back-projection and central slide theorem.
• Nuclear medicine: anatomical versus functional imaging, radioactivity, radioactive decay, radionuclide, dose and efficiency
• SPECT and PET: collimator, scintillators, anger camera, coincidence detection circuit, scatter and resolution
• Nuclear Magnetic Imaging: physical principles, magnetization, free induction decay, sequences and slice selection

5 hours out of 30 will be delivered through innovative teaching methods as “Blended Learning” and “Flipped Classroom”. Students will be actively involved studying and presenting to the class an assigned topic and an in-depth final guided discussion.

Laboratory Activity (15 hours)

The laboratory activity requires knowledge of programming in Matlab environment

• Hands on with biomedical images: the history of medical imaging. The representation of an image in Matlab: image definition, spatial coordinates. Image types: intensity, binary, indexed, RGB.
• 2D Fourier series: Matlab implementation of 2D discrete Fourier Transform for images and its properties
• Image enhancement: image histogram, punctual operators, histogram equalization, spatial filtering
• Edge detection and contours: gradient and Laplacian operators . Noise suppression filtering.
• Image reconstruction: x-ray, computed tomography, Radon transform

Project Activity  (5 hours)

A project laboratory is integral part of the course. The objective is to help students in translating the notions and methodologies learnt throughout the course in a specific case study. Projects will be assigned during the semester. Projects are expected to be delivered fixed deadlines by the end of the course. The evaluation of projects will be based on a final presentation to be discussed by the all project group. The project activity will include open discussions supervised by the course instructor and by tutors throughout the semester. Students who cannot take the project laboratory in this semester can work at the project on their own in the following semester. In this latter case, no support will be provided.

Students are required to know the principles and methods of biomedical signal processing as can be obtained after the attendance in the I level Course “Fondamenti di segnali biomedici”.

Assessment

The assessment will be based on a WRITTEN test  with exercises and open questions, time 60 min..

It will assign up to 26 points and will be considered sufficient when the score will be equal or higher than 16. The project part will assign up to 4 points. The Lab assignment will assign up to 1 point. Project and Lab assignment are not mandatory. Students can take the written part at any exam session within of the Academic Year of attendance.

No mid-term assessments will be scheduled.

The score of the written exams (up to 26), the project (up to 4)  and the practical assessment (up to 1) will be summed to compute the total score. 30 cum laude will be assigned when the total score is equal to  31.

To pass the exam the student must obtain an overall average grade of at least 18/30 .