AIMS AND CONTENT

LEARNING OUTCOMES

The course introduces algorithms for the reconstruction and processing of biomedical images. In particular, also through guided laboratory exercises, tomographic and MRI reconstruction, segmentation, iterative algorithms for PET and SPECT will be treated 

AIMS AND LEARNING OUTCOMES

The aim is to knowledge of biomedical images reconstruction and processing algotithms.

In particular this unit introduces: Filtered Back projection, MRI reconstruction, itertive methods for PTE and SPECT and

ITK/VTK software for registration and segmentation of biomedical images

At the end of the course the students will be able to elaborate biomedical images extracting features useful to diagnosis, to superimpose images coming from different acquisitions, to understand algorithms at the base of the main biomedical imaging techniques.

TEACHING METHODS

Combination of traditional lectures (28 hours) and laboratory sessions (20 hours). 

SYLLABUS/CONTENT

•    Tomographic Image Reconstruction:  Filtered Back Projection method, used filters, artefacts and resolution limit.
•    MRI Image reconstruction: main artefacts and methods for their reduction.
•    Iterative algorithms for functional images PET e SPECT (OS-EM)
•    Introduction of the  ITK e VTK toolkit for multi-modal image visualization, segmentation and registration

RECOMMENDED READING/BIBLIOGRAPHY

• Applied Medical Image Processing, Second Edition: A Basic Course, Wolfgang Birkfellner
• On-line: Principles of Computerized Tomography

TEACHERS AND EXAM BOARD

Exam Board

PATRIZIA BOCCACCI (President)

MARCO MASSIMO FATO

LESSONS

Class schedule

BIOMEDICAL IMAGE PROCESSING

EXAMS

ASSESSMENT METHODS

Oral and laboratory examination  

Exam schedule