461 citations · 717 across the 17 of their papers we have counts for
18 papers
Concurrence: A dependence criterion for time series, applied to biological data
Evangelos Sariyanidi, John D. Herrington, Lisa Yankowitz +8
Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often exhibit complex non-linear interactions…
Measuring Dependencies between Biological Signals with Self-supervision, and its Limitations
Evangelos Sariyanidi, John D. Herrington, Lisa Yankowitz +6
Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often exhibit complex non-linear interactions…
The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu +68
Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less…
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)
Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu +70
Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less…
Bayesian tensor regression using the Tucker decomposition for sparse spatial modeling
Daniel Spencer, Rajarshi Guhaniyogi, Russell Shinohara +1
Modeling with multidimensional arrays, or tensors, often presents a problem due to high dimensionality. In addition, these structures typically exhibit inherent sparsity, requiring…
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Bhakti Baheti, Satrajit Chakrabarty, Hamed Akbari +70
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been progress in developing gene…
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)…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…
The extent and drivers of gender imbalance in neuroscience reference lists
Jordan D. Dworkin, Kristin A. Linn, Erin G. Teich +3
Like many scientific disciplines, neuroscience has increasingly attempted to confront pervasive gender imbalances within the field. While much of the conversation has centered arou…
Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands
Eli J. Cornblath, Arian Ashourvan, Jason Z. Kim +13
A diverse white matter network and finely tuned neuronal membrane properties allow the brain to transition seamlessly between cognitive states. However, it remains unclear how stat…
Robust Spatial Extent Inference with a Semiparametric Bootstrap Joint Testing Procedure
Simon N. Vandekar, Theodore D. Satterthwaite, Cedric H. Xia +4
Spatial extent inference (SEI) is widely used across neuroimaging modalities to study brain-phenotype associations that inform our understanding of disease. Recent studies have sho…
The landscape of NeuroImage-ing research
Jordan D. Dworkin, Russell T. Shinohara, Danielle S. Bassett
As the field of neuroimaging grows, it can be difficult for scientists within the field to gain and maintain a detailed understanding of its ever-changing landscape. While collabor…
The emergent integrated network structure of scientific research
Jordan D. Dworkin, Russell T. Shinohara, Danielle S. Bassett
The practice of scientific research is often thought of as individuals and small teams striving for disciplinary advances. Yet as a whole, this endeavor more closely resembles a co…
Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging
D. Andrew Brown, Christopher S. McMahan, Russell T. Shinohara +1
Alzheimer's disease is a neurodegenerative condition that accelerates cognitive decline relative to normal aging. It is of critical scientific importance to gain a better understan…
Interpretable High-Dimensional Inference Via Score Projection with an Application in Neuroimaging
Simon N. Vandekar, Philip T. Reiss, Russell T. Shinohara
In the fields of neuroimaging and genetics, a key goal is testing the association of a single outcome with a very high-dimensional imaging or genetic variable. Often, summary measu…
Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap
Simon N. Vandekar, Theodore D. Satterthwaite, Adon Rosen +6
In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. Recent studies have shown that the most common…
Modular Segregation of Structural Brain Networks Supports the Development of Executive Function in Youth
Graham L. Baum, Rastko Ciric, David R. Roalf +12
The human brain is organized into large-scale functional modules that have been shown to evolve in childhood and adolescence. However, it remains unknown whether structural brain n…
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…