作者: 有雜色 時(shí)間: 2025-3-22 00:00
Sabine Dittrich,Ilse Jürgenliemkng the inner product of signals, a closed form expression is obtained, which allows its computation using spherical harmonics from a reduced set of acquired data, compatible with most popular diffusion MRI acquisition protocols. Results show that the proposed metric (1) is able to discriminate among作者: 過分 時(shí)間: 2025-3-22 01:57
https://doi.org/10.1007/978-3-322-84746-1etic resonance imaging. CSD models the diffusion-weighted signal as the convolution of a fiber orientation distribution function and a “single fiber response function”, representing the signal profile of a population of aligned fibers. The performance of CSD relies crucially on the robust and accura作者: 混合,攙雜 時(shí)間: 2025-3-22 06:02 作者: DNR215 時(shí)間: 2025-3-22 09:34 作者: Condense 時(shí)間: 2025-3-22 13:09
Manfred Bornhofen,Martin C. Bornhofenneuro- and body imaging. The promise of micro-scale analyses has been in the creation of . that provide information in place of physical histology, while tractography and its related methods offer maps of the neuronal wiring through .. While both approaches have had strong successes at the group lev作者: Condense 時(shí)間: 2025-3-22 18:04 作者: 投射 時(shí)間: 2025-3-22 22:57
Manfred Bornhofen,Martin C. Bornhofeniber tractography. Both are impacted by the free-water partial volume effect that arises at the border of cerebrospinal fluid or in presence of vasogenic edema. Hence, in order to robustly track white matter fibers close to cerebrospinal fluid and in presence of edema, or to extract consistent bioma作者: Negligible 時(shí)間: 2025-3-23 02:52
Manfred Bornhofen,Martin C. Bornhofenrocess is estimating fiber orientation distribution?(FOD), often done from a model such as constrained spherical deconvolution?(CSD). Multi-shell?(MS) multi-tissue CSD?(M-CSD) provides a robust WM FOD?by estimating the relative contribution to the dMRI?signal from each tissue type (WM, grey matter, 作者: fulcrum 時(shí)間: 2025-3-23 07:27 作者: Preamble 時(shí)間: 2025-3-23 10:07 作者: Engulf 時(shí)間: 2025-3-23 15:04 作者: 幸福愉悅感 時(shí)間: 2025-3-23 21:03
Manfred Bornhofen,Martin C. Bornhofenportance, longitudinal atlases?become necessary as references, most often created from cross-sectional data. New opportunities will be offered by creating longitudinal brain atlases from longitudinal subject-specific image data, where explicit modeling of subject’s variability in slope and intercept作者: 萬神殿 時(shí)間: 2025-3-24 00:57 作者: 無聊的人 時(shí)間: 2025-3-24 02:30 作者: 保留 時(shí)間: 2025-3-24 07:30 作者: 中國紀(jì)念碑 時(shí)間: 2025-3-24 12:13
Computational Diffusion MRI978-3-030-52893-5Series ISSN 1612-3786 Series E-ISSN 2197-666X 作者: 支架 時(shí)間: 2025-3-24 16:01 作者: FRONT 時(shí)間: 2025-3-24 22:01 作者: acetylcholine 時(shí)間: 2025-3-25 00:35
https://doi.org/10.1007/978-3-030-52893-5diffusion MRI; multidimensional diffusion MRI; combined diffusion-relaxometry MRI; computational techni作者: 命令變成大炮 時(shí)間: 2025-3-25 06:31
978-3-030-52895-9Springer Nature Switzerland AG 2020作者: Ingratiate 時(shí)間: 2025-3-25 10:09
1612-3786 usion process and signal generation, to new computational methods and estimation techniques for the .in vivo. recovery of microstructural and connectivity features, as well as diffusion-relaxometry and frontlin978-3-030-52895-9978-3-030-52893-5Series ISSN 1612-3786 Series E-ISSN 2197-666X 作者: 外露 時(shí)間: 2025-3-25 15:39
Conference proceedings 2020tributions covering a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational methods and estimation techniques for the .in vivo. recovery of microstructural and connectivity features, as well as diffusion-relaxometry and frontlin作者: AMPLE 時(shí)間: 2025-3-25 16:38 作者: 厭惡 時(shí)間: 2025-3-25 22:04 作者: Delude 時(shí)間: 2025-3-26 03:14
Current Challenges and Future Directions in Diffusion MRI: From Model- to Data- Driven Analysisective of diffusion MRI as a signal that is explained by a tractable biophysical model with one in which data driven machine learning can inform us about detection, localization, and assessment of both normal and abnormal brain tissue in both local (voxels) and global connectivity. Towards this end,作者: maudtin 時(shí)間: 2025-3-26 05:59
Spatial Sparse Estimation of Fiber Orientation Distribution Using Deep Alternating Directions Methodssessed using standard tractography and automatic white matter analysis algorithms. Compared with the comparison method, the proposed method has good consistency in sparse fiber reconstruction and fiber continuity.作者: 得體 時(shí)間: 2025-3-26 10:15 作者: 幸福愉悅感 時(shí)間: 2025-3-26 14:01 作者: 行為 時(shí)間: 2025-3-26 20:24 作者: 廚房里面 時(shí)間: 2025-3-27 00:45 作者: 種子 時(shí)間: 2025-3-27 02:34
https://doi.org/10.1007/978-3-658-21698-6and suppress their influences on final correlation maps by altering one pulsed-field-gradient (PFG) direction. Results from Monte-Carlo simulations in a three-dimensional confining domain with a bundle of capillaries orientated by a certain degree verified the correction. Further experiments on diff作者: 連累 時(shí)間: 2025-3-27 06:25 作者: COKE 時(shí)間: 2025-3-27 10:02 作者: 新娘 時(shí)間: 2025-3-27 13:36 作者: Thyroid-Gland 時(shí)間: 2025-3-27 19:13 作者: mechanical 時(shí)間: 2025-3-27 23:36 作者: penance 時(shí)間: 2025-3-28 02:56
https://doi.org/10.1007/978-3-322-84746-1errors in the alignment step of this procedure lead to an observable bias, and introduce an alternative algorithm based on rotational invariants that entirely avoids the problematic alignment step. The corresponding estimator is proven to be unbiased and consistent, which is verified experimentally.作者: 遺留之物 時(shí)間: 2025-3-28 08:48 作者: 使乳化 時(shí)間: 2025-3-28 11:21 作者: GAVEL 時(shí)間: 2025-3-28 18:23
Connectome 2.0: Cutting-Edge Hardware Ushers in New Opportunities for Computational Diffusion MRI can be measured accurately. Here we present an overview of the Connectome 2.0 project, which aims to bridge this gap by building the next-generation instrument for imaging microstructure and connectional anatomy in the human brain.作者: verdict 時(shí)間: 2025-3-28 20:16 作者: Ovulation 時(shí)間: 2025-3-29 02:13
1612-3786 e number of rich full-color visualizations.Biologically or c.This volume gathers papers presented at the Workshop on Computational Diffusion MRI (CDMRI 2019), held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), which took pl作者: freight 時(shí)間: 2025-3-29 06:17 作者: VOK 時(shí)間: 2025-3-29 10:39
Alternative Diffusion Anisotropy Metric from Reduced MRI Acquisitionsquired data, compatible with most popular diffusion MRI acquisition protocols. Results show that the proposed metric (1) is able to discriminate among different microstructure scenarios; (2) shows a robust behaviour in clinical studies.作者: 踉蹌 時(shí)間: 2025-3-29 12:34 作者: 使困惑 時(shí)間: 2025-3-29 17:37
Manfred Bornhofen,Martin C. Bornhofen. In this study, a novel approach based on the physarum solver was investigated. Through the experiments on synthetic and real data sets, potentials and limitations of the approach were displayed and discussed.作者: fibula 時(shí)間: 2025-3-29 23:15
Manfred Bornhofen,Martin C. Bornhofens of each measurement, a neural network is trained on synthetic groundtruth data. According to our evaluation, this methodology produces more consistent and more plausible results than previous approaches.作者: 時(shí)代 時(shí)間: 2025-3-30 00:16
Manfred Bornhofen,Martin C. Bornhofens of other diffusion MRI processing methods. The methods proposed herein outperform the state of the art on q-space data in terms of quality and inference time. Our methods also outperform the state of the art on a standard novelty detection benchmark, and hence are also promising for non-MRI novelty detection.作者: Negotiate 時(shí)間: 2025-3-30 05:40
https://doi.org/10.1007/978-3-658-33835-0 provide an accurate and efficient estimation of microstructural parameters in-silico and from DW-MRI data with moderately high b-values (4000?s/mm.). Further, we show, on in-vivo data, that the estimators trained from simulations can provide parameter estimates which are close to the values expected from histology.作者: neologism 時(shí)間: 2025-3-30 08:15 作者: 引起 時(shí)間: 2025-3-30 13:59
Manfred Bornhofen,Martin C. Bornhofenusion techniques with graph theory and principal component analysis (PCA). Our results suggest that the pattern of connectivity is altered and differences in connectivity patterns result in more vulnerable premature brain network.作者: 包裹 時(shí)間: 2025-3-30 19:53 作者: 山頂可休息 時(shí)間: 2025-3-30 23:10 作者: 碎片 時(shí)間: 2025-3-31 04:20 作者: 持續(xù) 時(shí)間: 2025-3-31 08:02
