831 citations · 939 across the 12 of their papers we have counts for
12 papers
3D Medical Image Segmentation based on multi-scale MPU-Net
Zeqiu. Yu, Shuo. Han, Ziheng. Song
The high cure rate of cancer is inextricably linked to physicians' accuracy in diagnosis and treatment, therefore a model that can accomplish high-precision tumor segmentation has…
Rapid Brain Meninges Surface Reconstruction with Layer Topology Guarantee
Peiyu Duan, Yuan Xue, Shuo Han +8
The meninges, located between the skull and brain, are composed of three membrane layers: the pia, the arachnoid, and the dura. Reconstruction of these layers can aid in studying v…
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…
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…
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…
Center-Extraction-Based Three Dimensional Nuclei Instance Segmentation of Fluorescence Microscopy Images
David Joon Ho, Shuo Han, Chichen Fu +3
Fluorescence microscopy is an essential tool for the analysis of 3D subcellular structures in tissue. An important step in the characterization of tissue involves nuclei segmentati…
Three dimensional blind image deconvolution for fluorescence microscopy using generative adversarial networks
Soonam Lee, Shuo Han, Paul Salama +2
Due to image blurring image deconvolution is often used for studying biological structures in fluorescence microscopy. Fluorescence microscopy image volumes inherently suffer from…
Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation
Chichen Fu, Soonam Lee, David Joon Ho +4
Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. Segmentation is a required step to characte…