图画文字
发表于 2025-3-25 04:05:42
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极为愤怒
发表于 2025-3-25 07:54:33
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Anonymous
发表于 2025-3-25 15:05:24
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irradicable
发表于 2025-3-25 16:07:06
Self-similarity Weighted Mutual Information: A New Nonrigid Image Registration Metricstration is an active field of research. We propose a self-similarity weighted graph-based implementation of .-mutual information (.-MI) for nonrigid image registration. The new .lf .imilarity .-. (SeSaMI) metric takes local structures into account and is robust against signal non-stationarity and i
全部
发表于 2025-3-25 21:50:48
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整理
发表于 2025-3-26 03:50:25
Selection of Optimal Hyper-Parameters for Estimation of Uncertainty in MRI-TRUS Registration of the ostate substructure and apex are not always visible which may make the seed placement sub-optimal. Based on an elastic model of the prostate created from MRI, where the prostate substructure and apex are clearly visible, we use a Bayesian approach to estimate the posterior distribution on deformatio
heterodox
发表于 2025-3-26 07:58:46
Globally Optimal Deformable Registration on a Minimum Spanning Tree Using Dense Displacement Samplin optimisation, which is prone to local minima. Recent advances in the mathematics and new programming methods enable these disadvantages to be overcome using discrete optimisation. In this paper, we present a new technique ., which employs a discrete .ns..isplacement .ampling for the deformable regi
PET-scan
发表于 2025-3-26 11:25:52
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deriver
发表于 2025-3-26 14:40:38
Regional Manifold Learning for Deformable Registration of Brain MR Imagesdical images advocate the use of manifold learning in order to confine the search space to anatomically plausible deformations. Existing methods construct manifolds based on a single metric over the entire image domain thus frequently miss regional brain variations. We address this issue by first le
aggressor
发表于 2025-3-26 17:43:35
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