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Xiaoliang Zhang

3 papers hereh-index 364.9k citations127 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • physics.med-ph2
  • eess.IV1
same name
  • Xiaoliang Zhang — 7 papers, h 4
  • Xiaoliang Zhang — 3 papers, h 8
  • Xiaoliang Zhang — 3 papers, h 3
  • Xiaoliang Zhang — 2 papers, h 5
  • Xiaoliang Zhang — 1 paper, h 2
  • Xiaoliang Zhang — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202022
most citedSuperDTI: Ultrafast diffusion tensor imaging and fiber tractography with deep learning

54 citations · 66 across the 3 of their papers we have counts for

collaborators

3 papers

physics.med-ph2022★ 11 cited

Hairpin RF Resonators for Transceiver Arrays with High Inter-channel Isolation and B1 Efficiency at Ultrahigh Field 7T MR Imaging

Komlan Payne, Leslie L. Ying, Xiaoliang Zhang

Electromagnetic decoupling among a close-fitting or high-density transceiver RF array elements is required to maintain the integrity of the magnetic flux density from individual ch…

physics.med-ph2021★ 1 cited

A Compact Planar Triple-Nuclear Coil for Small Animal 1H, 13C, and 31P Metabolic MR Imaging at 14.1 T

Andrew P. Leynes, Yiran Chen, Subramaniam Sukumar +2

Multi-nuclear radio-frequency (RF) coils at ultrahigh field strengths are challenging to develop due to the high operating frequency, increased electromagnetic interaction among th…

eess.IV2020★ 54 cited

SuperDTI: Ultrafast diffusion tensor imaging and fiber tractography with deep learning

Hongyu Li, Zifei Liang, Chaoyi Zhang +9

Purpose: To propose a deep learning-based reconstruction framework for ultrafast and robust diffusion tensor imaging and fiber tractography. Methods: We propose SuperDTI to learn t…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.