This repository provides a Python-based implementation of Computed Tomography (CT) reconstruction for 2D images.
The task is to reconstruct the image of a sample from its X-ray detector readings (also called sinogram). Given the experiment geometry details, it generates lines representing the X-ray path through the object and calculates their intersections with each pixel. These intercept lengths form an intercept matrix A. Using the detector readings
The CT reconstruction problem is expressed mathematically as: A λ = d
- A is the intercept matrix, containing lengths of X-ray intercepts on each pixel within the object.
- λ is the attenuation coefficient data for each pixel, which is the desired output.
- d is the sinogram vector, calculated as -
-
$I_o$ is the intensity of the X-ray source. -
$I$ is the intensity observed by the detectors.
The solution of the image ie λ gives us the image of the object.
Note that we are considering only a 2D cross-section of the object.
