most citedScaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV20241 cited

Tractography with T1-weighted MRI and associated anatomical constraints on clinical quality diffusion MRI

Tian Yu, Yunhe Li, Michael E. Kim +8

Diffusion MRI (dMRI) streamline tractography, the gold standard for in vivo estimation of brain white matter (WM) pathways, has long been considered indicative of macroscopic relat…

cs.CV2024

Nucleus subtype classification using inter-modality learning

Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios +14

Understanding the way cells communicate, co-locate, and interrelate is essential to understanding human physiology. Hematoxylin and eosin (H&E) staining is ubiquitously available b…

eess.IV2023

Deep conditional generative models for longitudinal single-slice abdominal computed tomography harmonization

Xin Yu, Qi Yang, Yucheng Tang +8

Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between…

cs.CV2023

Exploring shared memory architectures for end-to-end gigapixel deep learning

Lucas W. Remedios, Leon Y. Cai, Samuel W. Remedios +8

Deep learning has made great strides in medical imaging, enabled by hardware advances in GPUs. One major constraint for the development of new models has been the saturation of GPU…

eess.IV20232 cited

Scaling Up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation

Ho Hin Lee, Quan Liu, Shunxing Bao +7

With the inspiration of vision transformers, the concept of depth-wise convolution revisits to provide a large Effective Receptive Field (ERF) using Large Kernel (LK) sizes for med…