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AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution
Research article (Frontiers in Oncology, 2022) · cited 21× · AI/ML
AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution
Summary
AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution is a scholarly article[1].
Key Facts
AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution. Retrieved May 24, 2026, from https://4ort.xyz/entity/attr2u-net-a-fully-automated-model-for-mri-nasopharyngeal-carcinoma-segmentation-based-on-spatial-attention-and-residual
MLA“AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/attr2u-net-a-fully-automated-model-for-mri-nasopharyngeal-carcinoma-segmentation-based-on-spatial-attention-and-residual.
BibTeX@misc{4ortxyz_attr2u-net-a-fully-automated-model-for-mri-nasopharyngeal-carcinoma-segmentation-based-on-spatial-attention-and-residual_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution}}, year = {2026}, url = {https://4ort.xyz/entity/attr2u-net-a-fully-automated-model-for-mri-nasopharyngeal-carcinoma-segmentation-based-on-spatial-attention-and-residual}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): AttR2U-Net: A Fully Automated Model for MRI Nasopharyngeal Carcinoma Segmentation Based on Spatial Attention and Residual Recurrent Convolution — https://4ort.xyz/entity/attr2u-net-a-fully-automated-model-for-mri-nasopharyngeal-carcinoma-segmentation-based-on-spatial-attention-and-residual (retrieved 2026-05-24)
