no code implementations • 6 Oct 2021 • Riddhish Bhalodia, Ali Hatamizadeh, Leo Tam, Ziyue Xu, Xiaosong Wang, Evrim Turkbey, Daguang Xu
Both the classification and localization are trained in conjunction and once trained, the model can be utilized for both the localization and characterization of pneumonia using only the input image.
no code implementations • 30 Mar 2021 • Xiaosong Wang, Ziyue Xu, Leo Tam, Dong Yang, Daguang Xu
In this work, we introduce an image-text pre-training framework that can learn from these raw data with mixed data inputs, i. e., paired image-text data, a mixture of paired and unpaired data.
no code implementations • 22 Sep 2020 • Xiaosong Wang, Ziyue Xu, Dong Yang, Leo Tam, Holger Roth, Daguang Xu
We apply the attention-on-label scheme on the classification task of a synthetic noisy CIFAR-10 dataset to prove the concept, and then demonstrate superior results (3-5% increase on average in multiple disease classification AUCs) on the chest x-ray images from a hospital-scale dataset (MIMIC-CXR) and hand-labeled dataset (OpenI) in comparison to regular training paradigms.