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researcher

Shuo Han

12 papers hereh-index 151.6k citations52 works total

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

author position
  • first author1
  • middle author11

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • eess.IV9
  • cs.CV3
same name
  • Shuo Han — 26 papers, h 18
  • Shuo Han — 20 papers, h 34
  • Shuo Han — 10 papers, h 6
  • Shuo Han — 7 papers, h 3
  • Shuo Han — 6 papers, h 3
  • Shuo Han — 5 papers, h 3

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
20182023
most citedCHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation

831 citations · 939 across the 12 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

eess.IV2022

Masked Autoencoders for Low dose CT denoising

Dayang Wang, Yongshun Xu, Shuo Han +1

Low-dose computed tomography (LDCT) reduces the X-ray radiation but compromises image quality with more noises and artifacts. A plethora of transformer models have been developed r…

eess.IV2022

Deep filter bank regression for super-resolution of anisotropic MR brain images

Samuel W. Remedios, Shuo Han, Yuan Xue +4

In 2D multi-slice magnetic resonance (MR) acquisition, the through-plane signals are typically of lower resolution than the in-plane signals. While contemporary super-resolution (S…

eess.IV2022

Disentangling A Single MR Modality

Lianrui Zuo, Yihao Liu, Yuan Xue +5

Disentangling anatomical and contrast information from medical images has gained attention recently, demonstrating benefits for various image analysis tasks. Current methods learn…

eess.IV2022

Coordinate Translator for Learning Deformable Medical Image Registration

Yihao Liu, Lianrui Zuo, Shuo Han +3

The majority of deep learning (DL) based deformable image registration methods use convolutional neural networks (CNNs) to estimate displacement fields from pairs of moving and fix…

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