54 citations · 130 across the 13 of their papers we have counts for
13 papers
Optimal Transport for Kernel Gaussian Mixture Models
Jung Hun Oh, Rena Elkin, Anish Kumar Simhal +3
The Wasserstein distance from optimal mass transport (OMT) is a powerful mathematical tool with numerous applications that provides a natural measure of the distance between two pr…
Wasserstein Image Local Analysis: Histogram of Orientations, Smoothing and Edge Detection
Jiening Zhu, Harini Veeraraghavan, Larry Norton +2
The Histogram of Oriented Gradient is a widely used image feature, which describes local image directionality based on numerical differentiation. Due to its ill-posed nature, small…
Nested-block self-attention for robust radiotherapy planning segmentation
Harini Veeraraghavan, Jue Jiang, Sharif Elguindi +5
Although deep convolutional networks have been widely studied for head and neck (HN) organs at risk (OAR) segmentation, their use for routine clinical treatment planning is limited…
Deep cross-modality (MR-CT) educed distillation learning for cone beam CT lung tumor segmentation
Jue Jiang, Sadegh Riyahi Alam, Ishita Chen +4
Despite the widespread availability of in-treatment room cone beam computed tomography (CBCT) imaging, due to the lack of reliable segmentation methods, CBCT is only used for gross…
A Vectorial Approach to Unbalanced Optimal Mass Transport
Jiening Zhu, Rena Elkin, Jung Hun Oh +2
Unbalanced optimal mass transport (OMT) seeks to remove the conservation of mass constraint by adding a source term to the standard continuity equation in the Benamou-Brenier formu…
PSIGAN: Joint probabilistic segmentation and image distribution matching for unpaired cross-modality adaptation based MRI segmentation
Jue Jiang, Yu Chi Hu, Neelam Tyagi +5
We developed a new joint probabilistic segmentation and image distribution matching generative adversarial network (PSIGAN) for unsupervised domain adaptation (UDA) and multi-organ…