138 citations · 143 across the 4 of their papers we have counts for
4 papers
A False Discovery Rate Control Method Using a Fully Connected Hidden Markov Random Field for Neuroimaging Data
Taehyo Kim, Qiran Jia, Mony J. de Leon +1
False discovery rate (FDR) control methods are essential for voxel-wise multiple testing in neuroimaging data analysis, where hundreds of thousands or even millions of tests are co…
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data
Taehyo Kim, Hai Shu, Qiran Jia +1
Voxel-based multiple testing is widely used in neuroimaging data analysis. Traditional false discovery rate (FDR) control methods often ignore the spatial dependence among the voxe…
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation
Qiran Jia, Hai Shu
Convolutional neural networks (CNNs) have achieved remarkable success in automatically segmenting organs or lesions on 3D medical images. Recently, vision transformer networks have…
mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks
Hai Shu, Ronghua Shi, Qiran Jia +2
Deep neural networks (DNNs) have achieved great success in image classification, but can be very vulnerable to adversarial attacks with small perturbations to images. To improve ad…