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Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography
Research article (Algorithms, 2021) · cited 23× · AI/ML
Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography
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Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography is a scholarly article[1].
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Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography's instance of is recorded as scholarly article[2].
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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). Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography. Retrieved May 24, 2026, from https://4ort.xyz/entity/boundary-loss-based-2-5d-fully-convolutional-neural-networks-approach-for-segmentation-a-case-study-of-the-liver-and-tum
MLA“Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/boundary-loss-based-2-5d-fully-convolutional-neural-networks-approach-for-segmentation-a-case-study-of-the-liver-and-tum.
BibTeX@misc{4ortxyz_boundary-loss-based-2-5d-fully-convolutional-neural-networks-approach-for-segmentation-a-case-study-of-the-liver-and-tum_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography}}, year = {2026}, url = {https://4ort.xyz/entity/boundary-loss-based-2-5d-fully-convolutional-neural-networks-approach-for-segmentation-a-case-study-of-the-liver-and-tum}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography — https://4ort.xyz/entity/boundary-loss-based-2-5d-fully-convolutional-neural-networks-approach-for-segmentation-a-case-study-of-the-liver-and-tum (retrieved 2026-05-24)
