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High-Performance Open-Source AI for Breast Cancer Detection and Localization in MRI https://doi.org/10.1148/ryai.240550 @cuny.edu #AOCMP2025 #medphys #RadPhys #radiology
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Generative #AI method reduces radiation dose & produces parametric response map parameters using only inspiratory-phase CT https://doi.org/10.1148/ryai.240680 #AOCMP2025 #medphys #RadPhys #radiology
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Commentary on emerging method to diagnose AD, 3D Nested Hierarchical Transformer (3DNesT) model https://doi.org/10.1148/ryai.250686 #AOCMP2025 #medphys #RadPhys #radiology
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Commentary on MRSegmentator and the idea of the generalist-style model https://doi.org/10.1148/ryai.250624 #AOCMP2025 #medphys #RadPhys #radiology
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Summary of the current state of validation rigor & transparency in FDA marketing authorization of AI-enabled devices in radiology https://doi.org/10.1148/ryai.250369 @danafarber.bsky.social @fda.gov #AOCMP2025 #medphys #RadPhys #radiology
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#AI system that integrates eye gaze data & #radiology reports to improve diagnostic accuracy in #ChestXray interpretation https://doi.org/10.1148/ryai.240277 @uh.edu #AOCMP2025 #medphys #RadPhys #radiology
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Generative model, using a single inspiratory CT, outperformed existing algorithms in parametric response map evaluation https://doi.org/10.1148/ryai.240680 #AOCMP2025 #medphys #RadPhys #radiology
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Commentary on emerging method to diagnose AD, 3D Nested Hierarchical Transformer (3DNesT) model https://doi.org/10.1148/ryai.250686 #AOCMP2025 #medphys #RadPhys #radiology
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A milestone in the evolution of medical imaging AI from specialists to generalists https://doi.org/10.1148/ryai.250624 #AOCMP2025 #medphys #RadPhys #radiology
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#DeepLearning model to segment lumbar paraspinal muscles & quantify muscle volumes on MRI https://doi.org/10.1148/ryai.240833 @griffith.edu.au #AOCMP2025 #medphys #RadPhys #radiology
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MRSegmentator accurately segments 40 anatomic structures on MRI and generalized to CT https://doi.org/10.1148/ryai.240477 @kbressem.bsky.social #AOCMP2025 #medphys #RadPhys #radiology
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Novel #AI system addresses perceptual errors in radiology through multimodal analysis of gaze and interaction data https://doi.org/10.1148/ryai.240277 @uh.edu #AOCMP2025 #medphys #RadPhys #radiology
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Fine-tuning federated learning improves #ProstateCancer detection https://doi.org/10.1148/ryai.240485 @rug.nl @nkinl.bsky.social #AOCMP2025 #medphys #RadPhys #radiology
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Commentary on work that deploys powerful vision transformers to structural MRI without the need for high-performance computing https://doi.org/10.1148/ryai.250686 #AOCMP2025 #medphys #RadPhys #radiology
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Commentary on MRSegmentator and the idea of the generalist-style model https://doi.org/10.1148/ryai.250624 #AOCMP2025 #medphys #RadPhys #radiology
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#DeepLearning model to segment lumbar paraspinal muscles & quantify muscle volumes on MRI https://doi.org/10.1148/ryai.240833 @griffith.edu.au #AOCMP2025 #medphys #RadPhys #radiology
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Single Inspiratory Chest CT-based Generative Deep Learning Models to Evaluate Functional Small Airway Disease https://doi.org/10.1148/ryai.240680 #AOCMP2025 #medphys #RadPhys #radiology
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#DeepLearning model trained on breast MRI dataset achieved state-of-the-art performance in #BreastCancer detection and localization https://doi.org/10.1148/ryai.240550 @cuny.edu #AOCMP2025 #medphys #RadPhys #radiology
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Prediction of Early Neoadjuvant Chemotherapy Response of Breast Cancer through Deep Learning-based Pharmacokinetic Quantification of DCE MRI https://doi.org/10.1148/ryai.240769 #AOCMP2025 #medphys #RadPhys #radiology
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#FederatedLearning enhances #prostate cancer detection https://doi.org/10.1148/ryai.240485 @rug.nl @nkinl.bsky.social #AOCMP2025 #medphys #RadPhys #radiology
Image from article in Radiology: Artificial Intelligence
Novel #AI system addresses perceptual errors in radiology through multimodal analysis of gaze and interaction data https://doi.org/10.1148/ryai.240277 @uh.edu #AOCMP2025 #medphys #RadPhys #radiology
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Rigor vs. transparency in @US_FDA marketing authorization of AI-enabled #MedicalDevices https://doi.org/10.1148/ryai.250369 @danafarber.bsky.social @fda.gov #AOCMP2025 #medphys #RadPhys #radiology
Image from article in Radiology: Artificial Intelligence
Generative #AI method reduces radiation dose & produces parametric response map parameters using only inspiratory-phase CT https://doi.org/10.1148/ryai.240680 #AOCMP2025 #medphys #RadPhys #radiology
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Deep learning method for lumbar paraspinal muscle segmentation on MRI https://doi.org/10.1148/ryai.240833 @griffith.edu.au #AOCMP2025 #medphys #RadPhys #radiology
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Influence of Mammography Acquisition Parameters on #AI and Radiologist Interpretive Performance https://doi.org/10.1148/ryai.240861 @danafarber.bsky.social #AOCMP2025 #medphys #RadPhys #radiology
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MR-Transformer: A Vision Transformer-based Deep Learning Model for Total Knee Replacement Prediction Using MRI https://doi.org/10.1148/ryai.240373 @cem.bsky.social @cai2r.net #AOCMP2025 #medphys #RadPhys #radiology
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💡 Revolutionizing neuroimaging: DLMUSE segments brain MRIs in seconds, enabling large-scale studies without the need for complex setups -- Dive into the future of brain research! https://doi.org/10.1148/ryai.240299 @upenn.edu #AOCMP2025 #medphys #RadPhys #radiology
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Understanding how mammography acquisition parameters affect #AI and radiologist performance is crucial for safe clinical AI integration https://doi.org/10.1148/ryai.240861 @danafarber.bsky.social #AOCMP2025 #medphys #RadPhys #radiology
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#FederatedLearning enhances #prostate cancer detection https://doi.org/10.1148/ryai.240485 @rug.nl @nkinl.bsky.social #AOCMP2025 #medphys #RadPhys #radiology
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MR-Transformer predicts knee osteoarthritis progression to joint replacement using MRI https://doi.org/10.1148/ryai.240373 @cem.bsky.social @cai2r.net #AOCMP2025 #medphys #RadPhys #radiology
