# DenseUNet+: A novel hybrid segmentation approach based on multi-modality images for brain tumor segmentation

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/denseunet-a-novel-hybrid-segmentation-approach-based-on-multi-modality-images/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Halıt Çetıner,Sedat Metlek |
| Citations | 44 |
| DOI | 10.1016/j.jksuci.2023.101663 |
| Fields | Computer Science,Neuroscience |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://doi.org/10.1016/j.jksuci.2023.101663 |
| OpenAlex ID | https://openalex.org/W4385154950 |
| Type | article |
| Year | 2023 |

## Paper authors

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

## 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/)
- [Medical Image Segmentation Techniques](https://scholariq.org/topics/medical-image-segmentation-techniques/)

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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.