activity
20192021
most citedWeakly supervised segmentation from extreme points

20 citations · 34 across the 7 of their papers we have counts for

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Showing eess.IVShow all

5 papers · 1 filter

eess.IV2021

T-AutoML: Automated Machine Learning for Lesion Segmentation using Transformers in 3D Medical Imaging

Dong Yang, Andriy Myronenko, Xiaosong Wang +3

Lesion segmentation in medical imaging has been an important topic in clinical research. Researchers have proposed various detection and segmentation algorithms to address this tas…

eess.IV2021★ 1 cited

Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports

Riddhish Bhalodia, Ali Hatamizadeh, Leo Tam +4

Localization and characterization of diseases like pneumonia are primary steps in a clinical pipeline, facilitating detailed clinical diagnosis and subsequent treatment planning. A…

eess.IV2021★ 1 cited

Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures

Holger R. Roth, Dong Yang, Wenqi Li +5

Building robust deep learning-based models requires diverse training data, ideally from several sources. However, these datasets cannot be combined easily because of patient privac…

eess.IV2020★ 11 cited

Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan

Dong Yang, Ziyue Xu, Wenqi Li +17

The recent outbreak of COVID-19 has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. As a complimentary tool, chest CT has been shown to be able t…

eess.IV2020★ 1 cited

Enhancing Foreground Boundaries for Medical Image Segmentation

Dong Yang, Holger Roth, Xiaosong Wang +3

Object segmentation plays an important role in the modern medical image analysis, which benefits clinical study, disease diagnosis, and surgery planning. Given the various modaliti…