49 citations · 144 across the 16 of their papers we have counts for
16 papers
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling
Dixian Zhu, Bokun Wang, Zhi Chen +4
This paper considers a novel application of deep AUC maximization (DAM) for multi-instance learning (MIL), in which a single class label is assigned to a bag of instances (e.g., mu…
Automated segmentation of choroidal layers from 3-dimensional macular optical coherence tomography scans
Kyungmoo Lee, Alexis K. Warren, Michael D. Abramoff +8
Background: Changes in choroidal thickness are associated with various ocular diseases and the choroid can be imaged using spectral-domain optical coherence tomography (SDOCT) and…
Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification
Zhuoning Yuan, Yan Yan, Milan Sonka +1
Deep AUC Maximization (DAM) is a new paradigm for learning a deep neural network by maximizing the AUC score of the model on a dataset. Most previous works of AUC maximization focu…
COVID CT-Net: Predicting Covid-19 From Chest CT Images Using Attentional Convolutional Network
Shakib Yazdani, Shervin Minaee, Rahele Kafieh +2
The novel corona-virus disease (COVID-19) pandemic has caused a major outbreak in more than 200 countries around the world, leading to a severe impact on the health and life of man…
COVID TV-UNet: Segmenting COVID-19 Chest CT Images Using Connectivity Imposed U-Net
Narges Saeedizadeh, Shervin Minaee, Rahele Kafieh +2
The novel corona-virus disease (COVID-19) pandemic has caused a major outbreak in more than 200 countries around the world, leading to a severe impact on the health and life of man…
Fully Automated 3D Segmentation of MR-Imaged Calf Muscle Compartments: Neighborhood Relationship Enhanced Fully Convolutional Network
Zhihui Guo, Honghai Zhang, Zhi Chen +5
Automated segmentation of individual calf muscle compartments from 3D magnetic resonance (MR) images is essential for developing quantitative biomarkers for muscular disease progre…