no code implementations • 14 Nov 2023 • Hongyang Jiang, Mengdi Gao, Zirong Liu, Chen Tang, Xiaoqing Zhang, Shuai Jiang, Wu Yuan, Jiang Liu
In this work, we propose a human-in-the-loop, label-free early DR diagnosis framework called GlanceSeg, based on SAM.
no code implementations • 16 Jun 2023 • Hongyang Jiang, Mengdi Gao, Yan Hu, Qiushi Ren, Zhaoheng Xie, Jiang Liu
Therefore, in this work, we innovatively devise noise-robust training approach to mitigate the adverse effects of noisy labels in medical image classification.
no code implementations • 25 Apr 2023 • Hongyang Jiang, Jingqi Huang, Chen Tang, Xiaoqing Zhang, Mengdi Gao, Jiang Liu
Concretely, the HITL CAD system was implemented on the multiple instance learning (MIL), where eye-tracking gaze maps were beneficial to cherry-pick diagnosis-related instances.
no code implementations • 28 Feb 2023 • Tyler Will, Runyu Zhang, Eli Sadovnik, Mengdi Gao, Joshua Vendrow, Jamie Haddock, Denali Molitor, Deanna Needell
We introduce a new method based on nonnegative matrix factorization, Neural NMF, for detecting latent hierarchical structure in data.
1 code implementation • 23 Jun 2021 • Mengdi Gao, Ximeng Feng, Mufeng Geng, Zhe Jiang, Lei Zhu, Xiangxi Meng, Chuanqing Zhou, Qiushi Ren, Yanye Lu
BLRM utilizes maximum a posteriori probability (MAP) in the Bayesian statistics and the exponentially time-weighted technique to selectively correct the labels of noisy images.