Explore an open-source Python library for image reconstruction in Axial Computed Tomography (TAC) using analytical Radon transforms of phantom classes. Dive into the creation of mathematical phantoms composed of simple geometric figures and their Radon transform sampling to build exact sinograms. Learn how to test reconstruction algorithms on zero-noise data, comparing approximated and exact sinograms using the iradon function from scikit-image. Investigate the Gibbs phenomenon's impact on reconstruction accuracy near phantom discontinuities. Gain insights into medical imaging techniques, filter selection, and backwards transforms through this comprehensive EuroPython 2020 conference talk by Francesca Tedeschi.
Overview
Syllabus
Intro
Phantom
Code
Phantom of Radon
Gibbs Phenomenon
Continuous
Tutorial
Errors
Discontinuities
Comparison
Backwards Transforms
Choosing the Filter
Medical Imaging
Taught by
EuroPython Conference