A Dense Pyramid Convolutional Neural Network for MRI Brain Tumor Segmentation
Article
| Article Title | A Dense Pyramid Convolutional Neural Network for MRI Brain Tumor Segmentation |
|---|---|
| ERA Journal ID | 18042 |
| Article Category | Article |
| Authors | Xiong, Wei, Song, Haina, Xie, Honggang and Li, Yan |
| Journal Title | Journal of Supercomputing |
| Journal Citation | 81 |
| Article Number | 1030 |
| Number of Pages | 30 |
| Year | 2025 |
| Publisher | Springer |
| Place of Publication | United States |
| ISSN | 0920-8542 |
| 1573-0484 | |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/s11227-025-07805-7 |
| Web Address (URL) | https://link.springer.com/article/10.1007/s11227-025-07805-7 |
| Abstract | Brain tumor segmentation is a crucial aspect of medical image analysis that distinguishes brain tumors from adjacent normal tissues in magnetic resonance imaging (MRI) scans. The objective of this task is to generate a binary or multi-class |
| Keywords | Multi-scale feature extraction; Brain tumor segmentation; Dense pyramid convolutional neural network (DensePyConvNet); Long-range dependency; Strip pooling |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 460201. Artificial life and complex adaptive systems |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Byline Affiliations | Hubei University of Technology, China |
| School of Science, Engineering & Digital Technologies- Maths,Physics & Computing |
https://research.usq.edu.au/item/101565/a-dense-pyramid-convolutional-neural-network-for-mri-brain-tumor-segmentation
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