saphenous-vein
发表于 2025-3-26 22:43:45
https://doi.org/10.1007/978-3-031-45350-2medical image analysis; machine learning; deep learning; lesion classification; lesion detection; lesion
细微差别
发表于 2025-3-27 04:48:26
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控制
发表于 2025-3-27 08:24:14
A Deep Attention-Multiple Instance Learning Framework to Predict Survival of Soft-Tissue Sarcoma frotted from the Deep Attention-MIL model are used to divide the patients into low/high-risk groups and predict survival time. The framework was trained and validated on a local dataset including 220 patients, then it was used to predict the survival for 48 patients in an external validation dataset. T
北京人起源
发表于 2025-3-27 10:37:09
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名义上
发表于 2025-3-27 15:51:57
Fully Automated CAD System for Lung Cancer Detection and Classification Using 3D Residual U-Net withxtensive experimental results illustrate the effectiveness of our 3D residual U-Net model. These results demonstrate the exceptional detection performance achieved by our proposed model with a sensitivity of 97.65% and an average classification accuracy of 96.37%. Performance analysis demonstrates t
吹气
发表于 2025-3-27 18:39:37
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率直
发表于 2025-3-28 01:03:44
Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI-cancerous images are presented to the model, with the purpose of localizing anomalous tumor regions during test time. We use a public dataset for model development. Performance of the architecture is evaluated in reference to subtraction images created from DCE-MRI. Code has been made publicly avai
颠簸地移动
发表于 2025-3-28 02:36:08
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闲荡
发表于 2025-3-28 09:21:08
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命令变成大炮
发表于 2025-3-28 11:01:54
ColNav: Real-Time Colon Navigation for Colonoscopyure, providing actionable and comprehensible guidance to un-surveyed areas in real-time, while seamlessly integrating into the physician’s workflow. Through coverage experimental evaluation, we demonstrated that our system resulted in a higher polyp recall (PR) and high inter-rater reliability with