美学
发表于 2025-3-23 13:11:30
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胎儿
发表于 2025-3-23 14:58:39
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Evocative
发表于 2025-3-23 19:36:40
Label-Efficient Contrastive Learning-Based Model for Nuclei Detection and Classification in 3D Cardim Intensity Projection (MIP) to convert immunofluorescent images with multiple slices to 2D images, which can cause signals from different z-stacks to falsely appear associated with each other. To overcome this, we devised an Extended Maximum Intensity Projection (EMIP) approach that addresses issue
智力高
发表于 2025-3-23 22:43:47
Affordable Graph Neural Network Framework Using Topological Graph Contractionmory-efficient GNN training framework (C-QSIGN), which incorporates our proposed contraction method along with several other state-of-the-art (SOTA) methods. Furthermore, we benchmarked our proposed model performance in terms of prediction quality and GPU usage against other SOTA methods. We show th
杂色
发表于 2025-3-24 05:03:37
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救护车
发表于 2025-3-24 09:45:49
A Multitask Framework for Label Refinement and Lesion Segmentation in Clinical Brain ImagingD scans. In extensive experiments on both proprietary and public clinical brain imaging datasets, we demonstrate that our end-to-end framework offers strong performance improvements over prevailing baselines on both label refinement and lesion segmentation. Our proposed framework maintains performan
Charitable
发表于 2025-3-24 11:28:12
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圆柱
发表于 2025-3-24 17:20:01
Feasibility of Universal Anomaly Detection Without Knowing the Abnormality in Medical Imagesnomaly detection model during the validation phase using only normal images, and (3) proposing a simple decision-level ensemble method to leverage the advantage of different kinds of anomaly detection without knowing the abnormality. The results of our experiments indicate that none of the evaluated
生存环境
发表于 2025-3-24 19:20:43
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rectocele
发表于 2025-3-25 00:17:05
Masked Image Modeling for Label-Efficient Segmentation in Two-Photon Excitation Microscopy of intensity and foreground structures, and inter-channel correlations that are specific to microscopy images. We show that these methods are effective for generating representations of TPEM images, and identify novel insights on how MIM can be modified to yield more salient image representations f