Point spread function modeling and images restoration for cone-beam CT

TL;DR

This paper introduces a new point spread function modeling approach for cone-beam CT that enables direct calculation of PSF under various conditions, improving image restoration without extra measurements.

Contribution

The paper presents a general PSF model for cone-beam CT and a novel restoration algorithm that enhances image clarity and reduces noise without additional calibration.

Findings

The PSF model accurately predicts imaging degradation across different scanning conditions.

The restoration algorithm improves edge clarity and controls noise effectively.

Experimental results confirm the method's feasibility and effectiveness.

Abstract

X-ray cone-beam computed tomography (CT) has the notable features such as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection images degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed firstly. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection images restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection images restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods.