activity
20192025
most cited3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis

23 citations · 31 across the 16 of their papers we have counts for

collaborators
Showing eess.IVShow all

5 papers · 1 filter

eess.IV2024

DINeuro: Distilling Knowledge from 2D Natural Images via Deformable Tubular Transferring Strategy for 3D Neuron Reconstruction

Yik San Cheng, Runkai Zhao, Heng Wang +5

Reconstructing neuron morphology from 3D light microscope imaging data is critical to aid neuroscientists in analyzing brain networks and neuroanatomy. With the boost from deep lea…

eess.IV2023

Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training

Lei Bai, Dongang Wang, Michael Barnett +13

Accurately measuring the evolution of Multiple Sclerosis (MS) with magnetic resonance imaging (MRI) critically informs understanding of disease progression and helps to direct ther…

eess.IV2021★ 23 cited

3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis

Jianhui Yu, Chaoyi Zhang, Heng Wang +5

General point clouds have been increasingly investigated for different tasks, and recently Transformer-based networks are proposed for point cloud analysis. However, there are bare…

eess.IV2021

Voxel-wise Cross-Volume Representation Learning for 3D Neuron Reconstruction

Heng Wang, Chaoyi Zhang, Jianhui Yu +4

Automatic 3D neuron reconstruction is critical for analysing the morphology and functionality of neurons in brain circuit activities. However, the performance of existing tracing a…

eess.IV2021★ 4 cited

Single Neuron Segmentation using Graph-based Global Reasoning with Auxiliary Skeleton Loss from 3D Optical Microscope Images

Heng Wang, Yang Song, Chaoyi Zhang +4

One of the critical steps in improving accurate single neuron reconstruction from three-dimensional (3D) optical microscope images is the neuronal structure segmentation. However,…