18 citations · 19 across the 6 of their papers we have counts for
8 papers
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…
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…
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…
RCNN-SliceNet: A Slice and Cluster Approach for Nuclei Centroid Detection in Three-Dimensional Fluorescence Microscopy Images
Liming Wu, Shuo Han, Alain Chen +3
Robust and accurate nuclei centroid detection is important for the understanding of biological structures in fluorescence microscopy images. Existing automated nuclei localization…
MR Slice Profile Estimation by Learning to Match Internal Patch Distributions
Shuo Han, Samuel Remedios, Aaron Carass +2
To super-resolve the through-plane direction of a multi-slice 2D magnetic resonance (MR) image, its slice selection profile can be used as the degeneration model from high resoluti…
CHAOS Challenge -- Combined (CT-MR) Healthy Abdominal Organ Segmentation
A. Emre Kavur, N. Sinem Gezer, Mustafa Barış +24
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) have intr…