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

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

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9 papers · 1 filter

eess.IV2023★ 8 cited

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…

eess.IV2023

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…

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…

eess.IV2021★ 1 cited

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…

eess.IV2020★ 831 cited

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…

eess.IV2019★ 5 cited

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…