# Rolling-Unet: Revitalizing MLP’s Ability to Efficiently Extract Long-Distance Dependencies for Medical Image Segmentation

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/rolling-unet-revitalizing-mlp-s-ability-to-efficiently-extract-long-distance/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yutong Liu,Haijiang Zhu,Mengting Liu,Huaiyuan Yu,Zihan Chen,Jie Gao |
| Citations | 116 |
| DOI | 10.1609/aaai.v38i4.28173 |
| Fields | Medicine |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://ojs.aaai.org/index.php/AAAI/article/download/28173/28344 |
| OpenAlex ID | https://openalex.org/W4393149370 |
| Type | conference-paper |
| Year | 2024 |

## Paper authors

- [Zihan Chen](https://scholariq.org/researchers/zihan-chen/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-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.