Article
A NOVEL DEEP LEARNING MODEL, RDB CYCYLEGAN-CBAM FOR LOW-DOSE CT IMAGE DENOISING
2026-02-18
Abstract excerpt
Computed Tomography (CT) is one of the largest contributors to radiation exposure from medical imaging, which can induce DNA damage and increase cancer risk. Reducing CT radiation dose to improve patient safety inherently increases image noise and artifacts. Generative adversarial networks (GANs) have shown promise for unsupervised low-dose CT (LDCT) denoising. Building on this, RDBCycleGAN-CBAM, a CycleGAN-based...
Topics
Open a Topic to create a Post that cites this publication.
Identifiers and source
- Literature Corpus work
- 30507394-9e4e-5303-b7de-8bfe19d9f1ef
- DOI
- 10.64898/2026.02.17.706311
