Multi-modal low-dose medical imaging through instruction-guided unified AI.

ABSTRACT:

Background

Ionizing radiation from PET/CT warrants dose reduction. However, lowering dose can degrade image quality and affect diagnosis. Many machine-learning approaches exist. Nevertheless, most are built for a single task and are difficult to deploy across multi-modal workflows. We sought to develop and evaluate a unified model that handles common restoration tasks across modalities.

Methods

We developed the Multi-modal Instruction-guided Restoration Architecture (MIRA-Net), a U-Net-based framework with an adaptive guidance module. The module estimates modality and degradation indicators from the input and produces a low-dimensional instruction that modulates feature processing throughout the network, selecting task-appropriate pathways within a single model. Performance

SUBMITTER: Lang H 

PROVIDER: S-EPMC12855130 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature