activity
20202022
most citedNoisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation

4 citations · 8 across the 6 of their papers we have counts for

collaborators

7 papers

eess.IV2022★ 2 cited

Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification

ChengHui Yu, MingKang Tang, ShengGe Yang +7

Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the signific…

eess.IV2021★ 1 cited

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning

Alessa Hering, Lasse Hansen, Tony C. W. Mok +50

Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medi…

cs.LG2021

Multi-Trigger-Key: Towards Multi-Task Privacy Preserving In Deep Learning

Ren Wang, Zhe Xu, Alfred Hero

Deep learning-based Multi-Task Classification (MTC) is widely used in applications like facial attributes and healthcare that warrant strong privacy guarantees. In this work, we ai…

cs.MA2021

Decentralized Graph-Based Multi-Agent Reinforcement Learning Using Reward Machines

Jueming Hu, Zhe Xu, Weichang Wang +3

In multi-agent reinforcement learning (MARL), it is challenging for a collection of agents to learn complex temporally extended tasks. The difficulties lie in computational complex…

eess.IV2021★ 1 cited

All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation

Zhe Xu, Yixin Wang, Donghuan Lu +6

Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially,…

eess.IV2021★ 4 cited

Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation

Zhe Xu, Donghuan Lu, Yixin Wang +5

Manually segmenting the hepatic vessels from Computer Tomography (CT) is far more expertise-demanding and laborious than other structures due to the low-contrast and complex morpho…

cs.CV2020

Do Public Datasets Assure Unbiased Comparisons for Registration Evaluation?

Jie Luo, Guangshen Ma, Sarah Frisken +8

With the increasing availability of new image registration approaches, an unbiased evaluation is becoming more needed so that clinicians can choose the most suitable approaches for…