# Bridging 2D and 3D segmentation networks for computation-efficient volumetric medical image segmentation: An empirical study of 2.5D solutions

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/bridging-2d-and-3d-segmentation-networks-for-computation-efficient-volumetric/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yichi Zhang,Qingcheng Liao,Le Ding,Jicong Zhang |
| Citations | 144 |
| DOI | 10.1016/j.compmedimag.2022.102088 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4281707594 |
| PMID | 35780703 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Yichi Zhang](https://scholariq.org/researchers/yichi-zhang/)

## Paper primary topic

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Paper topics

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)
- [Medical Imaging and Analysis](https://scholariq.org/topics/medical-imaging-and-analysis/)

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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.