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🚀 Introducing #DLMUSE: a deep learning model for brain MRI segmentation that’s 10,000x faster than traditional methods! ⏱️ Segments in just 3.5 seconds with state-of-the-art accuracy https://doi.org/10.1148/ryai.240299 @upenn.edu #BIRAC25 #radiology
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Establishing normative, age-based, pediatric kidney length and volume percentiles from a large US dataset with a natural language processing model https://doi.org/10.1148/ryai.250056 #BIRAC25 #radiology
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Random Convolutions for Domain Generalization of Deep Learning-based Medical Image Segmentation Models https://doi.org/10.1148/ryai.240502 @tum.de #BIRAC25 #radiology
Image from article in Radiology: Artificial Intelligence
Homomorphic encryption was integrated into deep learning models for CT-based renal mass classification https://doi.org/10.1148/ryai.240798 #BIRAC25 #radiology
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Characterizing the Impact of Training Data on Generalizability: Application in Deep Learning to Estimate Lung Nodule Malignancy Risk https://doi.org/10.1148/ryai.240636 #BIRAC25 #radiology
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Dentate nucleus segmentation tool using #DeepLearning applied to brain MRI-based quantitative susceptibility mapping images https://doi.org/10.1148/ryai.240478 #BIRAC25 #radiology
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#Mirai model uses lesion features on #mammograms for lesion detection and #breast cancer risk prediction. https://doi.org/10.1148/ryai.240417 #BIRAC25 #radiology
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DLMUSE: Robust Brain Segmentation in Seconds Using #DeepLearning https://doi.org/10.1148/ryai.240299 @upenn.edu #BIRAC25 #radiology
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The recent move of this blog to Substack gives us a chance to begin anew radiologyai.substack.com/p/the-vasty-deep-we-begi... @cekahn.bsky.social @rsnasky.bsky.social #BIRAC25 #radiology
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AI Manipulation of the Peer Review Process: Dangers and Lessons radiologyai.substack.com/p/ai-manipulation-of-the... #BIRAC25 #radiology
Image from article in Radiology: Artificial Intelligence
Liver Imaging Feature Transformer model for diagnosis of focal liver lesions on #MRI https://doi.org/10.1148/ryai.240531 #BIRAC25 #radiology
