89 citations · 110 across the 6 of their papers we have counts for
6 papers
Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples
Sai Spandana Chintapalli, Rongguang Wang, Zhijian Yang +7
Availability of large and diverse medical datasets is often challenged by privacy and data sharing restrictions. For successful application of machine learning techniques for disea…
Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning
Junhao Wen, Mathilde Antoniades, Zhijian Yang +4
Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neu…
Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering
Zhijian Yang, Junhao Wen, Ahmed Abdulkadir +25
Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multipl…
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification
Ujjwal Baid, Satyam Ghodasara, Suyash Mohan +100
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR)…
Riccati-regularized Precision Matrices for Neuroimaging
Nicolas Honnorat, Christos Davatzikos
The introduction of graph theory in neuroimaging has pro- vided invaluable tools for the study of brain connectivity. These methods require the definition of a graph, which is typi…
Benchmarking confound regression strategies for the control of motion artifact in studies of functional connectivity
Rastko Ciric, Daniel H. Wolf, Jonathan D. Power +11
Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of confound regression methods to limit its imp…