# ResUNet+: A New Convolutional and Attention Block-Based Approach for Brain Tumor Segmentation

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/resunet-a-new-convolutional-and-attention-block-based-approach-for-brain-tumor/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sedat Metlek,Halıt Çetıner |
| Citations | 70 |
| DOI | 10.1109/access.2023.3294179 |
| Fields | Computer Science,Neuroscience |
| Open Access | true |
| OA Status | gold |
| OA URL | https://ieeexplore.ieee.org/ielx7/6287639/6514899/10177740.pdf |
| OpenAlex ID | https://openalex.org/W4383751079 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Sedat Metlek](https://scholariq.org/researchers/sedat-metlek/)
- [Halıt Çetıner](https://scholariq.org/researchers/hal-t-cet-ner/)

## Paper journal

- [IEEE Access](https://scholariq.org/journals/ieee-access/)

## Paper primary topic

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

## Paper topics

- [Brain Tumor Detection and Classification](https://scholariq.org/topics/brain-tumor-detection-and-classification/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Digital Imaging for Blood Diseases](https://scholariq.org/topics/digital-imaging-for-blood-diseases/)

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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.