# Semi-Supervised Unpaired Medical Image Segmentation Through Task-Affinity Consistency

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/semi-supervised-unpaired-medical-image-segmentation-through-task-affinity/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Jingkun Chen,Jianguo Zhang,Kurt Debattista,Jungong Han |
| Citations | 82 |
| DOI | 10.1109/tmi.2022.3213372 |
| Fields | Computer Science,Neuroscience |
| Open Access | true |
| OA Status | green |
| OA URL | https://wrap.warwick.ac.uk/170166/1/WRAP-semi-supervised-unpaired-medical-image-segmentation-through-task-affinity-consistency-2022.pdf |
| OpenAlex ID | https://openalex.org/W4304481262 |
| PMID | 36219664 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Kurt Debattista](https://scholariq.org/researchers/kurt-debattista/)

## 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/)
- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)

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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.