CAAT-Class Attention Augmented Transformers for Quantification of Post-Operative Glioblastoma with Follow-Up-Reference-Cited by-同舟云学术

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CAAT-Class Attention Augmented Transformers for Quantification of Post-Operative Glioblastoma with Follow-Up

Published:2024-05-27 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 IEEE International Symposium on Biomedical Imaging (ISBI)
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Author:

Kundu Swagata¹,Toumpanakis Dimitrios²,Wikstrom Johan²,Strand Robin³,Dhara Ashis Kumar¹

Affiliation:

1. National Institute of Technology Durgapur,Electrical Engineering Department,India

2. Uppsala University,Department of Surgical Sciences, Neuroradiology,Sweden

3. Uppsala University,Centre for Image Analysis,Department of Information Technology,Sweden

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635394.pdf?arnumber=10635394

Reference14 articles.

1. Glioblastoma Multiforme: An Overview of Emerging Therapeutic Targets

2. HTTU-Net: Hybrid Two Track U-Net for Automatic Brain Tumor Segmentation

3. MRI brain tumor segmentation using residual Spatial Pyramid Pooling-powered 3D U-Net

4. dResU-Net: 3D deep residual U-Net based brain tumor segmentation from multimodal MRI

5. Improved U-Net3+ with stage residual for brain tumor segmentation

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