Fibroid 发表于 2025-3-30 11:32:20
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,Evaluating Histopathology Foundation Models for Few-Shot Tissue Clustering: An Application to LC250, we create a clean version of LC25000. We then evaluate the quality of features extracted by these foundational models, using the clustering task as a benchmark. Our contributions are: 1) We publicly release our semi-automatic annotation pipeline along with the LC25000-clean dataset to facilitate a平常 发表于 2025-3-30 22:53:11
http://reply.papertrans.cn/29/2845/284440/284440_54.png倒转 发表于 2025-3-31 03:43:42
http://reply.papertrans.cn/29/2845/284440/284440_55.pngTartar 发表于 2025-3-31 06:48:34
,Synthetic Simplicity: Unveiling Bias in Medical Data Augmentation,irst demonstrate this vulnerability on a digit classification task, where the model spuriously utilizes the source of data instead of the digit to provide an inference. We provide further evidence of this phenomenon in a medical imaging problem related to cardiac view classification in echocardiogracreditor 发表于 2025-3-31 12:28:47
,Pre-processing and Quality Control of Large Clinical CT Head Datasets for Intracranial Arterial Cals (structural similarity index measure) to triage assessment of individual image series. Additionally, we propose superimposing thresholded binary masks of the series to inspect large quantities of data in parallel. We identify and exclude unrecoverable samples and registration failures..In total, oEmmenagogue 发表于 2025-3-31 16:18:46
http://reply.papertrans.cn/29/2845/284440/284440_58.png后退 发表于 2025-3-31 19:40:14
http://reply.papertrans.cn/29/2845/284440/284440_59.pngMultiple 发表于 2025-3-31 23:46:38
,Simple is More: Efficient Liver View Classification in Ultrasound Images Using Minimal Labeled DataimpleClassifier achieved an accuracy of 91.5% with 257 labeled frames, while ResNet-18 and MLP-Mixer required 801 labeled frames each to achieve 70.2% and 86% accuracy, respectively. These findings demonstrate that combining active learning with an AI classifier, regardless of its complexity, can im