Dilated multi-scale residual attention (DMRA) U-Net: three-dimensional (3D) dilated multi-scale residual attention U-Net for brain tumor segmentation

We developed a promising tumor segmentation model. Our solution is open sourced and is available at: https://github.com/Gold3nk/dmra-unet.

Authors

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Publication Details

Journal
Quantitative Imaging in Medicine and Surgery
Published
2024-09-23
DOI
https://doi.org/10.21037/qims-24-779
Citations
6
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
1.48

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article

Dilated multi-scale residual attention (DMRA) U-Net: three-dimensional (3D) dilated multi-scale residual attention U-Net for brain tumor segmentation

Chongxin Xu, Yingbo Liang, Tong Liu, Junding Sun et al.
6 citations
Quantitative Imaging in Medicine and Surgery
Brain Tumor Detection and Classification
1.48
article

Dilated multi-scale residual attention (DMRA) U-Net: three-dimensional (3D) dilated multi-scale residual attention U-Net for brain tumor segmentation

Chongxin Xu, Yingbo Liang, Tong Liu, Junding Sun, Yuzhuo Li, Lihong Zhang
article en
6 citations

Abstract

We developed a promising tumor segmentation model. Our solution is open sourced and is available at: https://github.com/Gold3nk/dmra-unet.

Quantitative Imaging in Medicine and SurgeryVol. 14(10)
Henan Polytechnic University (CN)
National Natural Science Foundation of China, Henan Polytechnic University
Openalex Percentile: Top 17%
Brain Tumor Detection and Classification
1.48
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Dilated multi-scale residual attention (DMRA) U-Net: three-dimensional (3D) dilated multi-scale residual attention U-Net for brain tumor segmentation — Chongxin Xu, Yingbo Liang, et al. · Quantitative Imaging in Medicine and Surgery (2024) | TGRS Research Map | TGRS