An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation

Research article (Neurocomputing, 2017) · cited 20× · AI/ML
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An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation

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An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-adaptive-kernel-regression-method-for-3d-ultrasound-reconstruction-using-speckle-prior-and-parallel-gpu-implementatio
MLA “An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-adaptive-kernel-regression-method-for-3d-ultrasound-reconstruction-using-speckle-prior-and-parallel-gpu-implementatio.
BibTeX @misc{4ortxyz_an-adaptive-kernel-regression-method-for-3d-ultrasound-reconstruction-using-speckle-prior-and-parallel-gpu-implementatio_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation}}, year = {2026}, url = {https://4ort.xyz/entity/an-adaptive-kernel-regression-method-for-3d-ultrasound-reconstruction-using-speckle-prior-and-parallel-gpu-implementatio}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An adaptive kernel regression method for 3D ultrasound reconstruction using speckle prior and parallel GPU implementation — https://4ort.xyz/entity/an-adaptive-kernel-regression-method-for-3d-ultrasound-reconstruction-using-speckle-prior-and-parallel-gpu-implementatio (retrieved 2026-05-24)

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