Stochastic particle gradient descent for infinite ensembles
The superior performance of ensemble methods with infinite models are well known. Most of
these methods are based on optimization problems in infinite-dimensional spaces with …
these methods are based on optimization problems in infinite-dimensional spaces with …
Community hospital experience using electromagnetic navigation bronchoscopy system integrating tidal volume computed tomography mapping
AA Raval, L Amir - Lung Cancer Management, 2016 - Taylor & Francis
Results of the first 50 consecutive patients referred for bronchoscopy or surgery by the tumor
review board to confirm suspect lung lesions identified by computed tomography …
review board to confirm suspect lung lesions identified by computed tomography …
Generalized Sinkhorn iterations for regularizing inverse problems using optimal mass transport
J Karlsson, A Ringh - SIAM Journal on Imaging Sciences, 2017 - SIAM
The optimal mass transport problem gives a geometric framework for optimal allocation and
has recently attracted significant interest in application areas such as signal processing …
has recently attracted significant interest in application areas such as signal processing …
Real-time 2D-3D deformable registration with deep learning and application to lung radiotherapy targeting
Radiation therapy presents a need for dynamic tracking of a target tumor volume. Fiducial
markers such as implanted gold seeds have been used to gate radiation delivery but the …
markers such as implanted gold seeds have been used to gate radiation delivery but the …
Diffeomorphic registration using Sinkhorn divergences
The diffeomorphic registration framework enables one to define an optimal matching
function between two probability measures with respect to a data-fidelity loss function. The …
function between two probability measures with respect to a data-fidelity loss function. The …
Indirect image registration with large diffeomorphic deformations
C Chen, O Oktem - SIAM Journal on Imaging Sciences, 2018 - SIAM
This paper adapts the large deformation diffeomorphic metric mapping framework for image
registration to the indirect setting, where a template is registered against a target that is …
registration to the indirect setting, where a template is registered against a target that is …
Automated calibration of model-driven reconstructions in atom probe tomography
C Fletcher, MP Moody, C Fleischmann… - Journal of Physics D …, 2022 - iopscience.iop.org
Traditional reconstruction protocols in atom probe tomography frequently feature image
distortions for multiphase materials, due to inaccurate geometric assumptions regarding …
distortions for multiphase materials, due to inaccurate geometric assumptions regarding …
Diffeomorphic Measure Matching with Kernels for Generative Modeling
This article presents a general framework for the transport of probability measures towards
minimum divergence generative modeling and sampling using ordinary differential …
minimum divergence generative modeling and sampling using ordinary differential …
A geometric variational approach to Bayesian inference
We propose a novel Riemannian geometric framework for variational inference in Bayesian
models based on the nonparametric Fisher–Rao metric on the manifold of probability …
models based on the nonparametric Fisher–Rao metric on the manifold of probability …
Supervised optimal transport
Optimal transport, a theory for optimal allocation of resources, is widely used in various fields
such as astrophysics, machine learning, and imaging science. However, many applications …
such as astrophysics, machine learning, and imaging science. However, many applications …