OVERVIEW

The influence and impact of digital images on modern society is tremendous, and image processing is now a critical component in science and technology. The rapid progress in computerized medical image reconstruction, and the associated developments in analysis methods and computer-aided diagnosis, has propelled medical imaging into one of the most important sub-fields in scientific imaging. The course takes its motivations from medical applications and uses real medical images and situations to clarify concepts and to build intuition and understanding. Designed for students who will become end users of digital image processing, the course emphasizes the effective use of image processing tools

AIMS AND CONTENT

LEARNING OUTCOMES

The aim of the course is to provide students with theoretical and practical tools to analyze, understand, and extract information from biomedical and biological images.
The course is intended to introduce the fundamental principles of the main diagnostic imaging modalities and to develop students' skills in digital image processing through theoretical lessons and practical laboratory activities. In particular, the teaching aims to provide basic knowledge related to:
a) image quality and pre/post-processing techniques;
b) segmentation, pattern recognition, and classification;
c) three-dimensional visualization.
The development of group projects using Matlab and open-source platforms also contributes to enhancing practical and collaborative skills, useful for future professional opportunities in healthcare, engineering, and information technology sectors.

AIMS AND LEARNING OUTCOMES

Attendance and active participation in the proposed learning activities (lectures and practical laboratory sessions), together with individual study, will enable students to:

• describe the fundamental principles of the main diagnostic imaging modalities used in biomedical and biological contexts (e.g., CT, MRI, ultrasound, microscopy);
• identify the key factors affecting biomedical image quality and explain the main pre- and post-processing techniques used to enhance images;
• apply digital image processing techniques to extract meaningful information from biomedical data;
• design basic image processing and analysis pipelines using appropriate software tools and programming environments;
• describe and compare segmentation, pattern recognition, and classification methods commonly used in biomedical image analysis;
• justify the choice of analysis and visualization techniques based on the specific application and image type;
• use three-dimensional visualization tools to interpret and present biomedical imaging data;
• critically assess the results obtained during laboratory activities, discussing their implications and limitations in diagnostic and research settings.

PREREQUISITES

It is assumed that the student knows a programming language (in particular Matlab)

TEACHING METHODS

The teaching consists in a combination of traditional lectures (24 hours), and  computer activities (48 hours - work group). Required course attendance as per the Didactic Regulations. The laboratory will be held by the teaching teachers, assisted by laboratory tutors. At the middle of the year, students must prepare a short presentation with the results obtained from the experimental activity. The organisation and dates of the laboratory activities will be communicated directly by the lecturers at the beginning of class.

SYLLABUS/CONTENT

The course program includes the presentation and discussion of the following topics:

• Imaging system
• The quality of a digital image
• Color images
• Medical imaging modalities
• The gray-level histogram
• Histogram transformations and look-up tables
• Convolution-based operations
• The Fourier domain and application in bioimaging
• Tomographic reconstruction
• Image degradation
• Noise and noise-reduction filters
• Morphological operations
• Image segmentation
• Feature recognition and classification
• Three-dimensional visualization
• Medical applications of imaging
• Frontiers of image processing in medicine

RECOMMENDED READING/BIBLIOGRAPHY

All slides used during lessons and other teaching materials will be available on aula@web. The books listed below are strongly suggested as supporting texts to complete the student's preparation, but students can also use other university level texts as long as they are published in the last 5 years.

1. J.G. Webster. Medical Instrumentation - Application and Design 4th Edition. Wiley.
2. Rafael C. Gonzales, Richard E. Woods - Elaborazione delle immagini digitali
3. Zhi - Pei Liang, Paul C. Lauterbur - Principles of Magnetic Resonance Imaging
4. Scott A. Huettel, Allen W. Song - Functional Magnetic Resonance Imaging
5. Geoff Dougherty - Digital image processing for medical applications
6. Paul Suetens - Foudamentals of medical imaging
7. Nadine Barrie Smith and Andrew Webb - Introduction to biomedical imaging

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

https://corsi.unige.it/en/corsi/11159

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Exam consists of

• eight imaging elaboration projects to be completed before the written test. This activity will be carried out in group of max 4 students, assisted by the teachers and tutors
• a written test .

ASSESSMENT METHODS

For the imaging elaboration projects, the student's level of autonomy in developing activities will be evaluated.
For the written test, the mastery of the theoretical topics covered during the lectures and behind the practical activities will be assessed.

At the middle of the year, students must prepare a short presentation with the results obtained from the experimental activity. The organisation and dates of the laboratory activities will be communicated directly by the lecturers at the beginning of class. The examination is passed if the marks for both activities (practical exercises and written test) are sufficient (grade > 18).

FURTHER INFORMATION

Ask the professor for other information not included in the teaching schedule