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Titlebook: Lesion Segmentation in Surgical and Diagnostic Applications; MICCAI 2022 Challeng Yiming Xiao,Guanyu Yang,Shuang Song Conference proceeding

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發(fā)表于 2025-3-23 11:58:55 | 只看該作者
Automated 3D Segmentation of?Renal Structures for?Renal Cancer Treatmentry-based renal cancer treatment. In this work, we describe our approach for 3D segmentation of renal vein, kidney, renal artery, and tumor from the KiPA 2022 dataset. We used the MONAI framework and the SegResNet architecture with a combination of Dice Focal loss and L2 regularization. We applied va
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發(fā)表于 2025-3-23 17:43:27 | 只看該作者
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發(fā)表于 2025-3-23 19:25:50 | 只看該作者
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發(fā)表于 2025-3-24 00:53:24 | 只看該作者
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發(fā)表于 2025-3-24 04:14:59 | 只看該作者
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發(fā)表于 2025-3-24 08:12:24 | 只看該作者
Accurate Detection of?Mediastinal Lesions with?nnDetectionsion of the self-configuring method nnDetection to the Mediastinal Lesion Analysis (MELA) Challenge 2022. By incorporating automatically generated pseudo masks, training high capacity models with large patch sizes in a multi GPU setup and an adapted augmentation scheme to reduce localization errors
17#
發(fā)表于 2025-3-24 14:37:03 | 只看該作者
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發(fā)表于 2025-3-24 18:54:06 | 只看該作者
19#
發(fā)表于 2025-3-24 19:29:47 | 只看該作者
Ultrasound Segmentation Using a?2D UNet with?Bayesian Volumetric Supportlumetric support to improve the accuracy of the segmentation of the query slice. Our results show that our proposed architecture achieves an 0.04 increase in the validation dice score compared to the benchmark network.
20#
發(fā)表于 2025-3-25 00:14:22 | 只看該作者
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