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Lei Zhou

Stony Brook University

4 papers hereh-index 7666 citations18 works total

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

author position
  • first author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV3
  • cs.CV1
affiliations
  • Stony Brook University
ORCID 0000-0002-7487-0792
same name
  • Lei Zhou — 23 papers, h 25
  • Lei Zhou — 14 papers, h 51
  • Lei Zhou — 10 papers, h 9
  • Lei Zhou — 8 papers, h 13
  • Lei Zhou — 8 papers, h 62
  • Lei Zhou — 8 papers, h 9

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
20222025
most citedSelf Pre-training with Masked Autoencoders for Medical Image Classification and Segmentation

9 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2025

NCF: Neural Correspondence Field for Medical Image Registration

Lei Zhou, Nimu Yuan, Katjana Ehrlich +1

Deformable image registration is a fundamental task in medical image processing. Traditional optimization-based methods often struggle with accuracy in dealing with complex deforma…

cs.CV2023

Token Sparsification for Faster Medical Image Segmentation

Lei Zhou, Huidong Liu, Joseph Bae +3

Can we use sparse tokens for dense prediction, e.g., segmentation? Although token sparsification has been applied to Vision Transformers (ViT) to accelerate classification, it is s…

eess.IV2022★ 9 cited

Self Pre-training with Masked Autoencoders for Medical Image Classification and Segmentation

Lei Zhou, Huidong Liu, Joseph Bae +3

Masked Autoencoder (MAE) has recently been shown to be effective in pre-training Vision Transformers (ViT) for natural image analysis. By reconstructing full images from partially…

eess.IV2022★ 2 cited

Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs

Lei Zhou, Joseph Bae, Huidong Liu +5

Well-labeled datasets of chest radiographs (CXRs) are difficult to acquire due to the high cost of annotation. Thus, it is desirable to learn a robust and transferable representati…

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