Medical Imaging and Image Processing
| Code | 3.2.3272.8 |
|---|---|
| Semester | 8th |
| Flow | I - Bioengineering |
| Category | Obligatory by selection |
| Credits | 4 |
| Class Hours - Lab Hours | 3 - 0 |
| Lecturers | Dimitrios Koutsouris, George Matsopoulos, Konstantina Nikita |
| Links | Helios, Course's Website |
| Web Platform |
Class 1:
Microsoft Teams
|
Description
Introduction to, and comparison of modern medical imaging modalities: Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Nuclear Medicine Imaging, Diagnostic Ultrasound. Medical image reconstruction: useful definitions (projection, linear integral), Fourier slice theorem, filtered back projection, iterative image reconstruction algorithms, artefacts in the reconstructed images. X-ray computed tomography (CT): Physics, instrumentation, data acquisition geometries, tomographic image reconstruction, helical CT. Magnetic Resonance Imaging (MRI): Nuclear Magnetic Resonance (NMR), Bloch equation, data acquisition, pulse sequences, relaxation processes and their measurement, MR imaging equation and reconstruction. Ultrasound (US) Imaging Techniques: physical principles, sound production and detection, beam forming techniques, pulse-echo imaging, real time imaging, Doppler imaging. Nuclear medicine and Single Photon Emission Computed Tomography (SPECT): radiopharmaceuticals, Anger Camera, principles of operation, instrumentation and image reconstruction. Positron Emission Tomography (PET): physics, radiopharmaceuticals, instrumentation, clinical applications. Basic principles of medical image processing and analysis: denoising, segmentation, texture analysis, three-dimensional visualization, computer aided diagnosis and treatment. Training exercises inbiomedical image reconstruction and processing using Matlab environment. Training exercises in biomedical image reconstruction and processing using Matlab environment.