Constrained H1-regularization schemes for diffeomorphic image registration [0.03%]
具约束的H1-范数正则化变分模型在图像配准中的应用
Andreas Mang,George Biros
Andreas Mang
We propose regularization schemes for deformable registration and efficient algorithms for their numerical approximation. We treat image registration as a variational optimal control problem. The deformation map is parametrized by its veloc...
ACTIVE MEAN FIELDS FOR PROBABILISTIC IMAGE SEGMENTATION: CONNECTIONS WITH CHAN-VESE AND RUDIN-OSHER-FATEMI MODELS [0.03%]
带活化项的mean field模型及其与CF和ROF模型的关系
Marc Niethammer,Kilian M Pohl,Firdaus Janoos et al.
Marc Niethammer et al.
Segmentation is a fundamental task for extracting semantically meaningful regions from an image. The goal of segmentation algorithms is to accurately assign object labels to each image location. However, image-noise, shortcomings of algorit...
Eigenvalues of Random Matrices with Isotropic Gaussian Noise and the Design of Diffusion Tensor Imaging Experiments [0.03%]
各向同性高斯噪声随机矩阵的特征值及扩散张量成像实验的设计
Dario Gasbarra,Sinisa Pajevic,Peter J Basser
Dario Gasbarra
Tensor-valued and matrix-valued measurements of different physical properties are increasingly available in material sciences and medical imaging applications. The eigenvalues and eigenvectors of such multivariate data provide novel and uni...
An Inexact Newton-Krylov Algorithm for Constrained Diffeomorphic Image Registration [0.03%]
受约束的形变图像配准的不精确牛顿-克里洛夫算法
Andreas Mang,George Biros
Andreas Mang
We propose numerical algorithms for solving large deformation diffeomorphic image registration problems. We formulate the nonrigid image registration problem as a problem of optimal control. This leads to an infinite-dimensional partial dif...
Yi Gao,Liangjia Zhu,Joshua Cates et al.
Yi Gao et al.
In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system pe...
A PROOF OF CONVERGENCE OF THE HORN AND SCHUNCK OPTICAL FLOW ALGORITHM IN ARBITRARY DIMENSION [0.03%]
Horn和Schunck光学流算法在任意维度中收敛性的证明
Louis LE Tarnec,François Destrempes,Guy Cloutier et al.
Louis LE Tarnec et al.
The Horn and Schunck (HS) method, which amounts to the Jacobi iterative scheme in the interior of the image, was one of the first optical flow algorithms. In this article, we prove the convergence of the HS method, whenever the problem is w...
E Katsevich,A Katsevich,A Singer
E Katsevich
In cryo-electron microscopy (cryo-EM), a microscope generates a top view of a sample of randomly oriented copies of a molecule. The problem of single particle reconstruction (SPR) from cryo-EM is to use the resulting set of noisy two-dimens...
ESTIMATION METHOD OF THE HOMODYNED K-DISTRIBUTION BASED ON THE MEAN INTENSITY AND TWO LOG-MOMENTS [0.03%]
基于一阶平均强度和两阶对数矩的同频干扰K分布参数估计方法
François Destrempes,Jonathan Porée,Guy Cloutier
François Destrempes
The homodyned K-distribution appears naturally in the context of random walks and provides a useful model for the distribution of the received intensity in a wide range of non-Gaussian scattering configurations, including medical ultrasonic...
Orientation Determination of Cryo-EM Images Using Least Unsquared Deviations [0.03%]
基于最小未平方偏差的冷冻电镜图像方向确定方法
Lanhui Wang,Amit Singer,Zaiwen Wen
Lanhui Wang
A major challenge in single particle reconstruction from cryo-electron microscopy is to establish a reliable ab initio three-dimensional model using two-dimensional projection images with unknown orientations. Common-lines-based methods est...
Two-Dimensional Tomography from Noisy Projections Taken at Unknown Random Directions [0.03%]
基于未知随机方向的噪声投影的二维层析成像
A Singer,H-T Wu
A Singer
Computerized tomography is a standard method for obtaining internal structure of objects from their projection images. While CT reconstruction requires the knowledge of the imaging directions, there are some situations in which the imaging ...