◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Sung‐Min Gho

4 papers hereh-index 13686 citations54 works total

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CV2
  • eess.IV2

identity via Semantic Scholar / OpenAlex

activity
20212025
collaborators

4 papers

eess.IV2025

Complex Swin Transformer for Accelerating Enhanced SMWI Reconstruction

Muhammad Usman, Sung-Min Gho

Susceptibility Map Weighted Imaging (SMWI) is an advanced magnetic resonance imaging technique used to detect nigral hyperintensity in Parkinsons disease. However, full resolution…

cs.CV2024

Biological Brain Age Estimation using Sex-Aware Adversarial Variational Autoencoder with Multimodal Neuroimages

Abd Ur Rehman, Azka Rehman, Muhammad Usman +5

Brain aging involves structural and functional changes and therefore serves as a key biomarker for brain health. Combining structural magnetic resonance imaging (sMRI) and function…

cs.CV2024

Multi-Task Adversarial Variational Autoencoder for Estimating Biological Brain Age with Multimodal Neuroimaging

Muhammad Usman, Azka Rehman, Abdullah Shahid +5

Despite advances in deep learning for estimating brain age from structural MRI data, incorporating functional MRI data is challenging due to its complex structure and the noisy nat…

eess.IV2021

Stacked U-Nets with Self-Assisted Priors Towards Robust Correction of Rigid Motion Artifact in Brain MRI

Mohammed A. Al-masni, Seul Lee, Jaeuk Yi +4

In this paper, we develop an efficient retrospective deep learning method called stacked U-Nets with self-assisted priors to address the problem of rigid motion artifacts in MRI. T…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.