figure 发表于 2025-3-23 12:56:17

,Wavelet Guided 3D Deep Model to Improve Dental Microfracture Detection,ikely fractured regions. Based on this fracture probability map we detect the presence of fracture and are able to differentiate a fractured tooth from a control tooth. We compare these results to a 2D CNN-based approach and we show that our approach provides superior detection results. We also show

出血 发表于 2025-3-23 14:47:35

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高原 发表于 2025-3-23 20:41:33

Seasonal Anoestrus in Wild Sowsith over 90% sensitivity and specificity. Although additional work is required before this approach is ready for clinical use, this study provides a basis for a screening tool to identify patients at risk within a time window that enables early proactive interventions intended to improve RRT outcome

拱墙 发表于 2025-3-24 00:04:48

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喃喃而言 发表于 2025-3-24 06:05:55

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cardiopulmonary 发表于 2025-3-24 09:03:42

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蜿蜒而流 发表于 2025-3-24 11:26:36

Michel Chonchol,Jessica Kendrick We propose to introduce a virtual user in the training process, modelled by simulating the user feedback from the current segmentation. We demonstrate our framework on the task of female pelvis MRI segmentation, using a new dataset. We evaluate our framework against existing work with the standard

孤僻 发表于 2025-3-24 17:58:03

Calcium Homeostasis in Kidney Disease layer-wise pruning delivers slightly better performance than network-wide pruning for small compression ratios (CRs) while for large CRs, network-wide pruning yields superior performance. For semantic segmentation, deep regression and final instance segmentation, 93.75%, 95%, and 80% of the model w

expound 发表于 2025-3-24 20:14:00

Joshua J. Neumiller,Irl B. Hirsch DCE-MR images obtained from public dataset. The segmentation results clearly show that the proposed network model provides the most accurate delineation results of the breast cancers in the DCE-MR images. The proposed model can be applied to other clinical practice sensitive to spatial information

sphincter 发表于 2025-3-25 00:34:00

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查看完整版本: Titlebook: Applications of Medical Artificial Intelligence; First International Shandong Wu,Behrouz Shabestari,Lei Xing Conference proceedings 2022 T