標(biāo)題: Titlebook: ; [打印本頁(yè)] 作者: osteomalacia 時(shí)間: 2025-3-21 16:52
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics影響因子(影響力)
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics影響因子(影響力)學(xué)科排名
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics網(wǎng)絡(luò)公開度
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics被引頻次
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics被引頻次學(xué)科排名
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics年度引用
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics年度引用學(xué)科排名
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics讀者反饋
書目名稱Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics讀者反饋學(xué)科排名
作者: aqueduct 時(shí)間: 2025-3-21 21:57 作者: emission 時(shí)間: 2025-3-22 02:29 作者: Promotion 時(shí)間: 2025-3-22 05:24 作者: ALT 時(shí)間: 2025-3-22 11:18 作者: CLIFF 時(shí)間: 2025-3-22 16:42
https://doi.org/10.1007/978-3-662-12556-4ously producing a time varying mapping connecting each image in the series. We demonstrate the efficacy of this method using segmentations of the entorhinal and surrounding cortex in subjects with early Alzheimer’s disease.作者: CLIFF 時(shí)間: 2025-3-22 19:04 作者: Assault 時(shí)間: 2025-3-22 22:07 作者: 刪減 時(shí)間: 2025-3-23 02:27 作者: 錯(cuò)誤 時(shí)間: 2025-3-23 09:00
Unbiased Diffeomorphic Mapping of?Longitudinal Data with Simultaneous Subject Specific Template Estiously producing a time varying mapping connecting each image in the series. We demonstrate the efficacy of this method using segmentations of the entorhinal and surrounding cortex in subjects with early Alzheimer’s disease.作者: DEMUR 時(shí)間: 2025-3-23 12:59 作者: LAITY 時(shí)間: 2025-3-23 16:13 作者: JECT 時(shí)間: 2025-3-23 18:36 作者: 知道 時(shí)間: 2025-3-23 22:36
https://doi.org/10.1007/978-1-4615-4979-6 data. Finally, coefficients encoding the disease dynamics are obtained from longitudinal cognitive measurements for each subject, and exploited to refine our methodology which is demonstrated to successfully predict the follow-up visits.作者: 彩色的蠟筆 時(shí)間: 2025-3-24 03:27 作者: 情節(jié)劇 時(shí)間: 2025-3-24 09:20
https://doi.org/10.1007/978-3-030-35276-9 on high-dimensional data. We show how different concepts from non-linear statistics and differential geometry can be implemented in Theano, and give examples of the implemented theory visualized on landmark representations of Corpus Callosum shapes.作者: progestogen 時(shí)間: 2025-3-24 12:49
Myofascial Pain and Dysfunctionpressed as a linear ODE in the Lie algebra. Solving this ODE directly is numerically stable and significantly faster than other LDDMM parallel transport methods. Results on 2D synthetic data and 3D brain MRI demonstrate that our algorithm is fast and conserves the inner products of the transported tangent vectors.作者: 歌劇等 時(shí)間: 2025-3-24 15:30
Graph Geodesics to Find Progressively Similar Skin Lesion Imageslesions. To quantitatively evaluate the quality of the returned path, we propose metrics to measure the number of transitions with respect to the lesion diagnosis, and the progression with respect to the clinical 7-point checklist. Compared to baseline experiments, our approach shows improvements to the quality of the returned paths.作者: 割讓 時(shí)間: 2025-3-24 22:33
White Matter Fiber Segmentation Using Functional Varifoldssiders both the geometry and microstructure measure (e.g. GFA) along the fiber pathway. We use it to cluster fibers with a dictionary learning and sparse coding-based framework, and present a preliminary analysis using HCP data.作者: Allowance 時(shí)間: 2025-3-25 00:14 作者: cataract 時(shí)間: 2025-3-25 03:36
Exact Function Alignment Under Elastic Riemannian Metricstricted to their change points. In many cases, the computational cost for matching is reduced by orders of magnitude. We demonstrate the superiority of this method over the DPA using several simulated and real datasets.作者: 裝飾 時(shí)間: 2025-3-25 10:45 作者: Memorial 時(shí)間: 2025-3-25 15:00
Efficient Parallel Transport in the Group of Diffeomorphisms via Reduction to the Lie Algebrapressed as a linear ODE in the Lie algebra. Solving this ODE directly is numerically stable and significantly faster than other LDDMM parallel transport methods. Results on 2D synthetic data and 3D brain MRI demonstrate that our algorithm is fast and conserves the inner products of the transported tangent vectors.作者: Anal-Canal 時(shí)間: 2025-3-25 18:40
https://doi.org/10.1007/978-1-4684-4778-1ies in the reconstruction or presenting alternative solutions. In this paper, we examine two different methods to sample vessel network graphs, a perturbation and a Gibbs sampler, and thereby estimate marginals. We quantitatively validate the accuracy of the approximated marginals using true marginals, computed by enumeration.作者: 樂意 時(shí)間: 2025-3-25 22:48 作者: FELON 時(shí)間: 2025-3-26 01:44 作者: 誰在削木頭 時(shí)間: 2025-3-26 05:50
Bridge Simulation and Metric Estimation on?Landmark Manifoldsional PDE with no closed-form solution in the nonlinear case. We show how the density can be numerically approximated by Monte Carlo sampling of conditioned Brownian bridges, and we use this to estimate parameters of the LDDMM kernel and thus the metric structure by maximum likelihood.作者: exclamation 時(shí)間: 2025-3-26 10:25 作者: BRINK 時(shí)間: 2025-3-26 15:01 作者: 熔巖 時(shí)間: 2025-3-26 19:17
Topology of Surface Displacement Shape Feature in Subcortical Structuresetween regions (e.g. subfields) of the structure and its change with disease remains unclear. In this paper, we present a first work to study the topology of the . shape feature via its persistence homology timeline features and model the polyadic interactions between the shape across the subfields 作者: prick-test 時(shí)間: 2025-3-27 00:48
Graph Geodesics to Find Progressively Similar Skin Lesion Imagespproaches to analyze skin images. In order to explore and gain insights into datasets of skin images, we propose a graph based approach to visualize a progression of similar skin images between pairs of images. In our graph, a node represents both a clinical and dermoscopic image of the same lesion,作者: 停止償付 時(shí)間: 2025-3-27 03:10
Uncertainty Estimation in Vascular Networkshape and image quality. Recent methods have addressed this problem as constrained maximum a posteriori (MAP) inference in a graphical model, formulated over an overcomplete network graph. Manual control and adjustments are often desired in practice and strongly benefit from indicating the uncertaint作者: metropolitan 時(shí)間: 2025-3-27 09:20
Extraction of Airways with Probabilistic State-Space Models and Bayesian Smoothingneurons and other tree structures can enable important clinical. applications. We present a framework for tracking tree structures comprising of elongated branches using probabilistic state-space models and Bayesian smoothing. Unlike most existing methods that proceed with sequential tracking of bra作者: 哭得清醒了 時(shí)間: 2025-3-27 12:55 作者: 背叛者 時(shí)間: 2025-3-27 15:11
Bridge Simulation and Metric Estimation on?Landmark Manifolds according to the transition distribution of a Riemannian Brownian motion arising from the Large Deformation Diffeomorphic Metric Mapping (LDDMM) metric. The distribution possesses properties similar to the regular Euclidean normal distribution but its transition density is governed by a high-dimens作者: Blanch 時(shí)間: 2025-3-27 20:46
White Matter Fiber Segmentation Using Functional Varifoldsialized distance measures, such as MCP, have been used for fiber similarity. However, these distance based approaches require point-wise correspondence and focus only on the geometry of the fibers. Recent publications have highlighted that using microstructure measures along fibers improves tractogr作者: 走路左晃右晃 時(shí)間: 2025-3-28 01:06 作者: 種子 時(shí)間: 2025-3-28 05:29 作者: Optometrist 時(shí)間: 2025-3-28 07:41 作者: 去掉 時(shí)間: 2025-3-28 12:40
Exact Function Alignment Under Elastic Riemannian Metricnt, including dynamic time warping (DTW), use penalized-. minimization that has significant shortcomings, including asymmetry. A recent mathematical framework, based on an elastic Riemannian metric and square-root velocity functions, overcomes these shortcomings. The time warping problem is currentl作者: 討好美人 時(shí)間: 2025-3-28 15:57
Varifold-Based Matching of Curves via Sobolev-Type Riemannian Metricsching to explore a new strategy of computing geodesics between unparametrized curves. We describe the numerical method used for solving the inexact matching problem, apply it to study the shape of mosquito wings and compare our method to curve matching in the LDDMM framework.作者: 香料 時(shí)間: 2025-3-28 21:32 作者: Progesterone 時(shí)間: 2025-3-29 02:39 作者: Plaque 時(shí)間: 2025-3-29 03:20
Efficient Parallel Transport in the Group of Diffeomorphisms via Reduction to the Lie Algebraroaches to parallel transport in large deformation diffeomorphic metric mapping (LDDMM) of images represent a momenta field, the dual of a tangent vector to the diffeomorphism group, as a scalar field times the image gradient. This “scalar momenta” constraint couples tangent vectors with the images 作者: 顯示 時(shí)間: 2025-3-29 08:31
Srdan Verstovsek,Ayalew Tefferi of cortical brain regions capture information about the structure of connections in the entire network. Hence, anatomical changes in network connectivity (e.g., caused by a certain disease) should translate into changes in the community structure of brain regions. This means that essential structur作者: 染色體 時(shí)間: 2025-3-29 15:00
https://doi.org/10.1007/978-3-662-65075-2h. Much work has therefore been done investigating the use of machine-learning techniques on functional and structural connectivity networks for ASD diagnosis. However, networks based on the morphology of the brain have yet to be similarly investigated, despite research findings that morphological f作者: DEI 時(shí)間: 2025-3-29 18:09 作者: 字謎游戲 時(shí)間: 2025-3-29 21:30
https://doi.org/10.1007/978-3-642-87074-3pproaches to analyze skin images. In order to explore and gain insights into datasets of skin images, we propose a graph based approach to visualize a progression of similar skin images between pairs of images. In our graph, a node represents both a clinical and dermoscopic image of the same lesion,作者: FID 時(shí)間: 2025-3-30 03:35 作者: 艱苦地移動(dòng) 時(shí)間: 2025-3-30 06:24 作者: brother 時(shí)間: 2025-3-30 08:50 作者: Lipoprotein(A) 時(shí)間: 2025-3-30 14:49 作者: Coronary 時(shí)間: 2025-3-30 18:42
Myocardial Ischemia and Lipid Metabolismialized distance measures, such as MCP, have been used for fiber similarity. However, these distance based approaches require point-wise correspondence and focus only on the geometry of the fibers. Recent publications have highlighted that using microstructure measures along fibers improves tractogr作者: spondylosis 時(shí)間: 2025-3-30 23:56
https://doi.org/10.1007/978-1-4615-4979-6ance on Alzheimer’s disease data. The disease progression is modeled as a trajectory on a group of diffeomorphisms in the context of large deformation diffeomorphic metric mapping (LDDMM). We first exhibit the limited predictive abilities of geodesic regression extrapolation on this group. Building 作者: 密切關(guān)系 時(shí)間: 2025-3-31 02:07 作者: 分開 時(shí)間: 2025-3-31 05:48
https://doi.org/10.1007/978-3-662-12556-4 scans. Geodesic trajectories which pass from a template onto a baseline image and then through each follow up image have been shown to overestimate atrophy rate in the entorhinal cortex, while the reverse is true for trajectories pass through the data in the opposite order. We propose a method to r作者: 燒瓶 時(shí)間: 2025-3-31 10:14 作者: 積云 時(shí)間: 2025-3-31 16:23 作者: babble 時(shí)間: 2025-3-31 19:41 作者: Lime石灰 時(shí)間: 2025-3-31 23:45
https://doi.org/10.1007/978-1-59259-319-44D Respiratory Correlated Computed Tomography (RCCT) Imaging. It is hypothesized that the quasi-periodic breathing induced motion of organs in the thorax can be represented by deformations spanning a very low dimension subspace of the full infinite dimensional space of diffeomorphic transformations.
