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U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans
Research article (Physics in Medicine and Biology, 2022) · cited 28× · AI/ML
U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans
Summary
U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans is a scholarly article[1].
Key Facts
U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans. Retrieved May 24, 2026, from https://4ort.xyz/entity/u-net-architecture-with-embedded-inception-resnet-v2-image-encoding-modules-for-automatic-segmentation-of-organs-at-risk
MLA“U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/u-net-architecture-with-embedded-inception-resnet-v2-image-encoding-modules-for-automatic-segmentation-of-organs-at-risk.
BibTeX@misc{4ortxyz_u-net-architecture-with-embedded-inception-resnet-v2-image-encoding-modules-for-automatic-segmentation-of-organs-at-risk_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans}}, year = {2026}, url = {https://4ort.xyz/entity/u-net-architecture-with-embedded-inception-resnet-v2-image-encoding-modules-for-automatic-segmentation-of-organs-at-risk}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans — https://4ort.xyz/entity/u-net-architecture-with-embedded-inception-resnet-v2-image-encoding-modules-for-automatic-segmentation-of-organs-at-risk (retrieved 2026-05-24)
