Computed Tomography and ASTRA Toolbox training course
Module 1: Introduction
- 1.1 Introduction to Computed Tomography
: Welcome to the Introductory module of the "Computed Tomography and ASTRA Toolbox" training course.
- 1.1 Introduction to Computed Tomography: Welcome to the Introductory module of the "Computed Tomography and ASTRA Toolbox" training course.
- 1.2 What is Computed Tomography?: When 2D radiography images are not sufficient, Computed Tomography (CT) comes to the rescue.
- 1.3 A brief history of Computed Tomography : Since the discovery of X-rays by Wilhelm Rontgen and his first medical images, a lot of progress has been made. In this video, the most important moments in the history of Computed Tomography are discussed.
- 1.4 Basic X-ray physics: The life of an X-ray photon, while short, is filled with interesting physics.
- 1.4.1 : X-ray Generation: X-rays are born in an X-ray tube.
- 1.4.2 : X-ray/matter Interaction: As X-rays traverse through an object, it might get attenuated.
- 1.4.3 : X-ray Detection: If an X-ray made it through the object, it gets measured in a detector cell.
- 1.5 Basic Mathematics of Computed Tomography: The life of a bunch of X-ray photons can also be described by a simplified mathematical model.
- 1.6 A Typical CT Workflow: Many different application fields can benefit from using Computed Tomography imaging. Most of these applications share a common workflow.
Module 2: Introduction to the ASTRA Toolbox
- 2.1 Introduction to the ASTRA Toolbox: Welcome to the ASTRA Toolbox Introductory module of the "Computed Tomography and ASTRA Toolbox" training course.
- 2.2 What is the ASTRA Toolbox?: The ASTRA Toolbox is an open source tool for efficient and flexible tomographic reconstruction algorithms.
- 2.3 ASTRA Toolbox organization: Internally, the ASTRA Toolbox contains three layers: low level projection algorithms, reconstruction methods, and the user interface.
- 2.4 ASTRA Toolbox modules: The ASTRA Toolbox consists of several modules working with each other to build flexible algorithms.
- 2.4.1 Volume Geometry: The ASTRA volume geometry stores information about the reconstruction volume (e.g., the pixel or voxel size).
- 2.4.2 Volume Data: An ASTRA volume data object stores volumetric data.
- 2.4.3 Projection Geometry: The ASTRA projection geometry stores information about the trajectory of the X-ray source and detector.
- 2.4.4 Projection Data: An ASTRA projection data object stores projection data.
- 2.4.5 Projector: An ASTRA projector defines the projection model.
- 2.4.6 Algorithm: An ASTRA algorithm object contains the logic to compute projection images and reconstructions.
- 2.5 ASTRA Toolbox Installation (Windows+MATLAB): Demo on how to install the ASTRA Toolbox on a Windows system using a MATLAB front end.
- 2.6 ASTRA Demo: Demo on how to configure the various modules to reconstruct a simple 2D toy example.
Module 3: Analytical Reconstruction Methods
- 3.1 Introduction to Analytical Reconstruction: Welcome to the Analytical Reconstruction module of the "Computed Tomography and ASTRA Toolbox" training course.
- 3.2 Analytical Projection: The projection model of CT expressed using analytical mathematics.
- 3.3 Fourier Slice Theorem: The Fourier Slice Theorem is the basis of the Filtered Backprojection reconstruction method.
- 3.4 Proof of the Fourier Slice Theorem: The Fourier Slice Theorem is easy to proof.
- 3.5 Filtered Backprojection (FBP): The Filtered Backprojection (FBP) is a very efficient, and therefore widely used, reconstruction method.
- 3.6 FBP in the ASTRA Toolbox: How can a FBP reconstruction be computed using the ASTRA Toolbox?
Module 4: Algebraic Reconstruction Methods
- 4.1 Introduction to Algebraic Reconstruction Methods: Welcome to the Algebraic Reconstruction module of the "Computed Tomography and ASTRA Toolbox" training course.
- 4.2 Algebraic Tomography: The projection model of CT expressed using algebra.
- 4.3 Iterative Reconstruction: In algebraic reconstruction methods, reconstructions are computed done iteratively.
- 4.4 Simultaneous Iterative Reconstruction Technique (SIRT): The Simultaneous Iterative Reconstruction Technique (SIRT) is the most popular algebraic reconstruction method.
- 4.5 SIRT in the ASTRA Toolbox: How can a SIRT reconstruction be computed using the ASTRA Toolbox?
- 4.6 Minimum Constraint: A minimum constraint is a simple example of how prior knowledge can benefit reconstructions.
- 4.7 Minimum Constraint in the ASTRA Toolbox: How can a minimum constraint be specified with the ASTRA Toolbox?
- 4.8 Other Algebraic Reconstruction Methods: Other more advanced algebraic reconstruction methods can offer better results, yet often come with an additional computational cost.