GAIR-U-Net: 3D guided attention inception residual u-net for brain tumor segmentation using multimodal MRI images

Author:

Rutoh Evans Kipkoech,Zhi Guang Qin,Bahadar Noor,Raza Rehan,Hanif Muhammad Shehzad

Publisher

Elsevier BV

Reference39 articles.

1. Aboussaleh, I., Riffi, J., Mahraz, A.M., Tairi, H., 2021. Brain Tumor Segmentation Based on Deep Learning’s Feature Representation.

2. 3DUV-NetR+: a 3D hybrid semantic architecture using transformers for brain tumor segmentation with MultiModal MR images;Aboussaleh;Results Eng.,2024

3. Single level UNet3D with multipath residual attention block for brain tumor segmentation;Akbar;J. King Saud Univ. – Comput. Inf. Sci.,2022

4. A novel approach for fully automatic intra-tumor segmentation with 3D U-Net architecture for gliomas;Baid;Front. Comput. Neurosci.,2020

5. Brain tumors segmentation using a hybrid filtering with U-Net architecture in multimodal MRI volumes;Esmaeilzadeh Asl;Int. J. Inf. Technol.,2023

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Advanced U-Net Model for Precise Brain Tumor Segmentation in MRI Images;REST Journal on Data Analytics and Artificial Intelligence;2024-07-13

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