# Advances in Medical Image Segmentation: A Comprehensive Review of Traditional, Deep Learning and Hybrid Approaches

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/advances-in-medical-image-segmentation-a-comprehensive-review-of-traditional/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yan Xu,Rixiang Quan,Weiting Xu,Yi‐Wen Huang,Xiaolong Chen,Fengyuan Liu |
| Citations | 256 |
| DOI | 10.3390/bioengineering11101034 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2306-5354/11/10/1034/pdf?version=1729073909 |
| OpenAlex ID | https://openalex.org/W4403456736 |
| PMID | 39451409 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Yi‐Wen Huang](https://scholariq.org/researchers/yi-wen-huang/)

## Paper journal

- [Bioengineering](https://scholariq.org/journals/bioengineering/)

## Paper primary topic

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

## Paper topics

- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

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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.