# UNet with ResNextify and IB modules for low-dose CT image denoising

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/unet-with-resnextify-and-ib-modules-for-low-dose-ct-image-denoising/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Swati Chauhan,Nidhi Malik,Rekha Vig |
| Citations | 14 |
| DOI | 10.1007/s41870-024-01898-8 |
| Fields | Computer Science,Engineering,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4396799934 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Nidhi Malik](https://scholariq.org/researchers/nidhi-malik/)

## Paper primary topic

- [Medical Imaging Techniques and Applications](https://scholariq.org/topics/medical-imaging-techniques-and-applications/)

## Paper topics

- [Medical Imaging Techniques and Applications](https://scholariq.org/topics/medical-imaging-techniques-and-applications/)
- [Image and Signal Denoising Methods](https://scholariq.org/topics/image-and-signal-denoising-methods/)
- [Advanced X-ray and CT Imaging](https://scholariq.org/topics/advanced-x-ray-and-ct-imaging/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.