33 citations · 111 across the 21 of their papers we have counts for
3 papers · 1 filter
Semi-supervised Learning Approach to Generate Neuroimaging Modalities with Adversarial Training
Harrison Nguyen, Simon Luo, Fabio Ramos
Magnetic Resonance Imaging (MRI) of the brain can come in the form of different modalities such as T1-weighted and Fluid Attenuated Inversion Recovery (FLAIR) which has been used t…
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels
Hieu H. Pham, Tung T. Le, Dat Q. Tran +2
Chest radiography is one of the most common types of diagnostic radiology exams, which is critical for screening and diagnosis of many different thoracic diseases. Specialized algo…
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
Pantelis Elinas, Edwin V. Bonilla, Louis Tiao
We propose a framework that lifts the capabilities of graph convolutional networks (GCNs) to scenarios where no input graph is given and increases their robustness to adversarial a…