# Deep Learning-Based MRI Brain Tumor Segmentation With EfficientNet-Enhanced UNet

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-based-mri-brain-tumor-segmentation-with-efficientnet-enhanced-unet/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Pradeep Kumar Tiwary,Prashant Johri,Alok Katiyar,Mayur Kumar Chhipa |
| Citations | 61 |
| DOI | 10.1109/access.2025.3554405 |
| Fields | Computer Science,Neuroscience |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1109/access.2025.3554405 |
| OpenAlex ID | https://openalex.org/W4408791511 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Prashant Johri](https://scholariq.org/researchers/prashant-johri/)

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

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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.