Search Results for author:
Found 12 papers, 3 papers with code
Rare Events Analysis and Computation for Stochastic Evolution of Bacterial Populations
In this paper, we develop a computational approach for computing most likely trajectories describing rare events that correspond to the emergence of non-dominant genotypes.
Automatic classification of deformable shapes
Let $\mathcal{D}$ be a dataset of smooth 3D-surfaces, partitioned into disjoint classes $\mathit{CL}_j$, $j= 1, \ldots, k$.
CLAIRE -- Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging Applications
CLAIRE allows us not only to register images of clinically relevant size in a few seconds but also to register images at unprecedented resolution in a reasonable time.
Stochastic Neural Networks for Automatic Cell Tracking in Microscopy Image Sequences of Bacterial Colonies
Our initial tests using experimental image sequences (i. e., real data) of E. coli colonies also yield convincing results, with a registration accuracy ranging from 90% to 100%.
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i. e., 2012-2018.
CLAIRE: A distributed-memory solver for constrained large deformation diffeomorphic image registration
We present the formulation, discuss algorithmic features, describe the software package, and introduce an improved preconditioner for the reduced space Hessian to speed up the convergence of our solver.
PDE-constrained optimization in medical image analysis
We review related literature and give examples on the formulation, discretization, and numerical solution of PDE-constrained optimization problems for medical imaging.
A Lagrangian Gauss-Newton-Krylov Solver for Mass- and Intensity-Preserving Diffeomorphic Image Registration
We use an optimal control formulation, in which the velocity field of a hyperbolic PDE needs to be found such that the distance between the final state of the system (the transformed/transported template image) and the observation (the reference image) is minimized.
Distributed-memory large deformation diffeomorphic 3D image registration
We are able to solve the registration problem for images of this size in less than five seconds on 64 x86 nodes of TACC's "Maverick" system.
A Semi-Lagrangian two-level preconditioned Newton-Krylov solver for constrained diffeomorphic image registration
We compare the performance of our solver against our initial implementation that uses the same spatial discretization but a standard, explicit, second-order Runge-Kutta scheme for the numerical time integration of the transport equations and a single-level preconditioner.
Computational Efficiency
Constrained Diffeomorphic Image Registration
+2
Constrained $H^1$-regularization schemes for diffeomorphic image registration
This allows us to explicitly control the compressibility of the deformation map and by that the determinant of the deformation gradient.
An inexact Newton-Krylov algorithm for constrained diffeomorphic image registration
We augment this regularization scheme with a constraint on the divergence of the velocity field rendering the deformation incompressible and thus ensuring that the determinant of the deformation gradient is equal to one, up to the numerical error.
Computational Efficiency
Constrained Diffeomorphic Image Registration
+1
