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A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images

Research article (International Journal of Medical Informatics, 2022) · cited 49× · AI/ML
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A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images

Summary

A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images is a scholarly article[1].

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  • A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images's instance of is recorded as scholarly article[2].

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  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images. Retrieved May 24, 2026, from https://4ort.xyz/entity/a-dense-residual-u-net-for-multiple-sclerosis-lesions-segmentation-from-multi-sequence-3d-mr-images
MLA “A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/a-dense-residual-u-net-for-multiple-sclerosis-lesions-segmentation-from-multi-sequence-3d-mr-images.
BibTeX @misc{4ortxyz_a-dense-residual-u-net-for-multiple-sclerosis-lesions-segmentation-from-multi-sequence-3d-mr-images_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images}}, year = {2026}, url = {https://4ort.xyz/entity/a-dense-residual-u-net-for-multiple-sclerosis-lesions-segmentation-from-multi-sequence-3d-mr-images}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images — https://4ort.xyz/entity/a-dense-residual-u-net-for-multiple-sclerosis-lesions-segmentation-from-multi-sequence-3d-mr-images (retrieved 2026-05-24)

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