AIMS AND CONTENT

LEARNING OUTCOMES

Il corso introduce algoritmi per la ricostruzione e l'elaborazione delle immagini biomediche. In particolare si trattano, anche attraverso esercitazioni di laboratorio guidate, ricostruzione tomografiche e MRI, segmentazione, algoritmi iterativi per PET e SPECT

LEARNING OUTCOMES (FURTHER INFO)

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

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