# Fast LLMMSE filter for low-dose CT imaging

## TL;DR

This paper introduces a fast, adaptive blockwise filtering algorithm based on the LLMMSE principle for real-time low-dose CT imaging, effectively reducing noise while preserving details.

## Contribution

It proposes a novel linear-time algorithm for sinogram filtering using a nonstationary Gaussian noise model and moving sum technique, improving speed and performance.

## Key findings

- Better noise reduction in reconstructed images
- Preserves image details effectively
- Operates in linear time regardless of block size

## Abstract

Low-dose X-ray CT technology is one of important directions of current research and development of medical imaging equipment. A fast algorithm of blockwise sinogram filtering is presented for realtime low-dose CT imaging. A nonstationary Gaussian noise model of low-dose sinogram data is proposed in the low-mA (tube current) CT protocol. Then, according to the linear minimum mean square error principle, an adaptive blockwise algorithm is built to filter contaminated sinogram data caused by photon starvation. A moving sum technique is used to speed the algorithm into a linear time one, regardless of the block size and thedata range. The proposedfast filtering givesa better performance in noise reduction and detail preservation in the reconstructed images,which is verified in experiments on simulated and real data compared with some related filtering methods.