4 papers
MindGrab for BrainChop: Fast and Accurate Skull Stripping for Command Line and Browser
Armina Fani, Mike Doan, Isabelle Le +4
Deployment complexity and specialized hardware requirements hinder the adoption of deep learning models in neuroimaging. We present MindGrab, a lightweight, fully convolutional mod…
False Discovery Rate and Localizing Power
Anderson M. Winkler, Paul A. Taylor, Thomas E. Nichols +1
False discovery rate (FDR) is commonly used for correction for multiple testing in neuroimaging studies. However, when using two-tailed tests, making directional inferences about t…
Go Figure: Transparency in neuroscience images preserves context and clarifies interpretation
Paul A. Taylor, Himanshu Aggarwal, Peter Bandettini +39
Visualizations are vital for communicating scientific results. Historically, neuroimaging figures have only depicted regions that surpass a given statistical threshold. This practi…
State-of-the-Art Stroke Lesion Segmentation at 1/1000th of Parameters
Alex Fedorov, Yutong Bu, Xiao Hu +2
Efficient and accurate whole-brain lesion segmentation remains a challenge in medical image analysis. In this work, we revisit MeshNet, a parameter-efficient segmentation model, an…