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Titlebook: Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data ; 6th Joint Internatio M. Jorge Cardoso

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發(fā)表于 2025-3-28 14:47:58 | 只看該作者
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DCNN-Based Automatic Segmentation and Quantification of Aortic Thrombus Volume: Influence of the Traential during follow-up?to evaluate the progress of the patient along time, comparing it to the pre-operative situation, and to detect complications. In this context, accurate assessment of the aneurysm or thrombus volume pre- and post-operatively is required. However, a quantifiable and trustworthy
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發(fā)表于 2025-3-29 02:29:29 | 只看該作者
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發(fā)表于 2025-3-29 13:41:47 | 只看該作者
Real Data Augmentation for Medical Image Classification only appear in a very small portion of the entire dataset. Nowadays, large collections of medical images are readily available. However, it is costly and may not even be feasible for medical experts to manually comb through a huge unlabeled dataset to obtain enough representative examples of the ra
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發(fā)表于 2025-3-29 18:22:10 | 只看該作者
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發(fā)表于 2025-3-30 02:36:02 | 只看該作者
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發(fā)表于 2025-3-30 07:01:22 | 只看該作者
Expected Exponential Loss for Gaze-Based Video and Volume Ground Truth Annotationobject segmentation, pixel-wise annotations are extremely expensive to collect, especially in video and 3D volumes. To reduce this annotation burden, we propose a novel framework to allow annotators to simply observe the object to segment and record where they have looked at with a $200 eye gaze tra
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