生气的边缘
发表于 2025-3-23 09:44:11
Non-rigid Groupwise Image Registration for Motion Compensation in Quantitative MRIm, black-blood variable flip-angle .. mapping in the carotid artery region, and apparent diffusion coefficient (ADC) mapping in the abdomen. The method was compared to a conventional pairwise alignment that uses a mutual information similarity measure. Registration accuracy was evaluated by computin
强有力
发表于 2025-3-23 17:31:21
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紧张过度
发表于 2025-3-23 20:49:03
https://doi.org/10.1057/9780230508439 a public dataset (CUMC12). Our proposed approach achieves a similar level of accuracy as other state-of-the-art methods but with processing times as short as 1.5 minutes. We also demonstrate preliminary qualitative results in the time-sensitive registration contexts of registering MR brain volumes
troponins
发表于 2025-3-24 00:57:52
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Urgency
发表于 2025-3-24 03:12:18
Anuradha Sood,Tarun Sharma,Aradhna Sharmaggregation and a decomposition of similarity and regularisation term into two convex optimisation steps. This approach enables non-parametric registration with billions of degrees of freedom with computation times of less than a minute. We apply our method to two different common medical image regis
新娘
发表于 2025-3-24 07:29:26
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Flagging
发表于 2025-3-24 11:20:46
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芳香一点
发表于 2025-3-24 16:10:52
https://doi.org/10.1007/978-3-030-60262-8ethods was evaluated on two publicly available image datasets, one of cerebral angiograms and the other of a spine cadaver, using standardized evaluation methodology. Results showed that the proposed method outperformed the current state-of-the-art methods and achieved registration accuracy of 0.5 m
低能儿
发表于 2025-3-24 20:25:12
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ostrish
发表于 2025-3-25 00:33:59
,In and Out of Cabinet, 1964–2002,n initialization and rely on the robustness of machine learning to the outliers and label updates via pyramidal deformable registration to gain better learning and predictions. In this sense, the proposed methodology has potential to be adapted in other learning problems as the manual labelling is u