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Titlebook: Computational Methods and Clinical Applications for Spine Imaging; Proceedings of the W Jianhua Yao,Tobias Klinder,Shuo Li Conference proce

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樓主: Systole
31#
發(fā)表于 2025-3-26 21:58:58 | 只看該作者
32#
發(fā)表于 2025-3-27 02:13:58 | 只看該作者
33#
發(fā)表于 2025-3-27 08:57:08 | 只看該作者
2212-9391 such a comprehensive topic in the field.Thorough coverage oThis book contains the full papers presented at the MICCAI 2013 workshop Computational Methods and Clinical Applications for Spine Imaging. The workshop brought together researchers representing several fields, such as Biomechanics, Enginee
34#
發(fā)表于 2025-3-27 09:35:14 | 只看該作者
Studying Vibrational Communicationentation results can be acquired within only a few iterations. Our experiments validate the capability of the proposed method with promising segmentation performance, even though the resolution and the contrast of our datasets are low.
35#
發(fā)表于 2025-3-27 14:31:17 | 只看該作者
Rafael L. Rodríguez,Flavia Barbosa shape boundaries, the Willmore energy helps to capture the detail shape and curvature information of the vertebrae. Experiment on CT images of normal and fractured spinal vertebrae demonstrate promising results in 3D segmentation.
36#
發(fā)表于 2025-3-27 18:10:11 | 只看該作者
Studying Vibrational Communication various Gaussian noise levels. The experimental results show that the noise immunity and the segmentation accuracy of our framework are much higher than scalar level sets approaches. Additionally, the construction of the shape model using 2D-PCA is computationally more efficient than PCA.
37#
發(fā)表于 2025-3-27 22:26:57 | 只看該作者
38#
發(fā)表于 2025-3-28 03:56:32 | 只看該作者
Amy L. Shelton,Jeffrey M. Zacksstudies of syndesmophyte development and growth. After one year, the 3D algorithm showed an increase in syndesmophyte volume in 75?% of patients, while radiography showed an increase in only 15?% of patients.
39#
發(fā)表于 2025-3-28 06:59:51 | 只看該作者
40#
發(fā)表于 2025-3-28 13:18:28 | 只看該作者
Stufen der Anordnung in Affinen R?umene obtained with the multi-level model were significantly better than those obtained with the traditional shape model. These initial results warrant further investigation of potential benefits that the multi-level statistical shape models can have in spine image analysis.
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