Which mathematical reconstruction method is most commonly used by modern CT scanners?

The most commonly used mathematical reconstruction method in modern CT scanners is filtered back-projection. This technique has been a foundational method in computed tomography due to its simplicity and speed, allowing for rapid reconstruction of images from raw data. Filtered back-projection works by applying a filter to the projection data to reduce artifacts and improve image quality, followed by back-projecting the filtered data to create the final image.

Modern applications of CT technology have indeed started to incorporate newer techniques like iterative reconstruction, which improves image quality and reduces radiation dose. However, filtered back-projection remains predominant in many systems because of its established history and efficiency, especially in non-emergency situations where speed is critical.

In contrast, maximum likelihood estimation and wavelet transformation are less commonly used for general reconstruction purposes in CT. Maximum likelihood estimation is often used in more specialized tasks or advanced imaging strategies, while wavelet transformation may have applications in image processing rather than direct reconstruction of CT images. Therefore, while other methods can enhance CT imaging in certain contexts, filtered back-projection continues to be the standard method in many contemporary CT scanners.