TAFG-MAN: Timestep-Adaptive Frequency-Gated Latent Diffusion for Efficient and High-Quality Low-Dose CT Image Denoising

TL;DR

TAFG-MAN introduces a novel latent diffusion framework with a Timestep-Adaptive Frequency-Gated mechanism for efficient, high-quality low-dose CT denoising, balancing noise suppression and detail preservation.

Contribution

The paper proposes TAFG-MAN, a new latent diffusion model with a frequency-gated conditioning mechanism that improves detail preservation in low-dose CT denoising.

Findings

Achieves better detail preservation and perceptual quality.

Maintains similar inference cost as baseline models.

Effective conditioning mechanism confirmed by ablation studies.

Abstract

Low-dose computed tomography (LDCT) reduces radiation exposure but also introduces substantial noise and structural degradation, making it difficult to suppress noise without erasing subtle anatomical details. In this paper, we present TAFG-MAN, a latent diffusion framework for efficient and high-quality LDCT image denoising. The framework combines a perceptually optimized autoencoder, conditional latent diffusion restoration in a compact latent space, and a lightweight Timestep-Adaptive Frequency-Gated (TAFG) conditioning design. TAFG decomposes condition features into low- and high-frequency components, predicts timestep-adaptive gates from the current denoising feature and timestep embedding, and progressively releases high-frequency guidance in later denoising stages before cross-attention. In this way, the model relies more on stable structural guidance at early reverse steps and introduces fine details more cautiously as denoising proceeds, improving the balance between noise suppression and detail preservation. Experiments show that TAFG-MAN achieves a favorable quality-efficiency trade-off against representative baselines. Compared with its base variant without TAFG, it further improves detail preservation and perceptual quality while maintaining essentially the same inference cost, and ablation results confirm the effectiveness of the proposed conditioning mechanism.