Image reconstruction

Image reconstruction is a crucial step in computed tomography (CT) that involves converting acquired raw data into meaningful and visually interpretable images. It is the fundamental process that enables the generation of detailed cross-sectional or 3D representations of the imaged object.

The image reconstruction process begins with the acquisition of raw data, which consists of a series of 2D projection images captured as the X-ray source and detector rotate around the object. Each projection image represents the attenuated X-ray beams passing through the object and reaching the detector.

The raw data contains information about the absorption of X-rays by the object in different directions. To create a detailed image of the object, this data needs to be transformed into a 2D or 3D volume. This is achieved by applying mathematical algorithms that reconstruct the position, absorption, and distribution of X-rays within the object.

The most common algorithm used for image reconstruction in CT is the backprojection algorithm. This algorithm works in a backward manner by backprojecting the measured projection data onto the voxels in the image volume. By integrating information from multiple projection angles, the absorption values for each voxel in the volume are determined. This process is repeated for each voxel to reconstruct the complete image volume.

An important challenge in image reconstruction is to reduce artifacts and ensure high image quality. Artifacts can be caused by various factors, such as incomplete projection data, scatter radiation, or motion artifacts. More advanced reconstruction algorithms, such as iterative methods, can be used to minimize these artifacts and improve image quality.

After image reconstruction, various image processing techniques can be applied to enhance the resulting image and increase diagnostic accuracy. These include filtering, noise reduction, contrast adjustment, and fusion of multiple images.

Image reconstruction is a crucial step in CT that enables obtaining detailed information about the internal structure of objects. It forms the basis for analysis, diagnosis, and visualization of diseases, injuries, or defects in various medical and industrial applications.