107 citations · 213 across the 20 of their papers we have counts for
21 papers
Landmark shape spaces with induced metrics
Sarang Joshi, Peter W. Michor, Stefan Sommer
We present a unification of Kendall's landmark shape spaces, where rigid motions are factored out and scale fixed on landmark configurations equipped with Euclidean geometry, with…
Neural Operator Learning for Ultrasound Tomography Inversion
Haocheng Dai, Michael Penwarden, Robert M. Kirby +1
Neural operator learning as a means of mapping between complex function spaces has garnered significant attention in the field of computational science and engineering (CS&E). In t…
Analyzing the Domain Shift Immunity of Deep Homography Estimation
Mingzhen Shao, Tolga Tasdizen, Sarang Joshi
Homography estimation serves as a fundamental technique for image alignment in a wide array of applications. The advent of convolutional neural networks has introduced learning-bas…
Modeling the Shape of the Brain Connectome via Deep Neural Networks
Haocheng Dai, Martin Bauer, P. Thomas Fletcher +1
The goal of diffusion-weighted magnetic resonance imaging (DWI) is to infer the structural connectivity of an individual subject's brain in vivo. To statistically study the variabi…
Bridge Simulation and Metric Estimation on Lie Groups and Homogeneous Spaces
Mathias Højgaard Jensen, Lennard Hilgendorf, Sarang Joshi +1
We present schemes for simulating Brownian bridges on complete and connected Lie groups and homogeneous spaces. We use this to construct an estimation scheme for recovering an unkn…
Integrated Construction of Multimodal Atlases with Structural Connectomes in the Space of Riemannian Metrics
Kristen M. Campbell, Haocheng Dai, Zhe Su +3
The structural network of the brain, or structural connectome, can be represented by fiber bundles generated by a variety of tractography methods. While such methods give qualitati…