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Modeling whole-body, CT-derived anatomic volumes to establish reference charts for the adult lifespan https://doi.org/10.1148/ryai.250506 #ACVC2026 #Cardiology #CVRad #radiology
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Transformer-based Fusion of Longitudinal Multimodal Radiomic Features from Chest Radiography and CT in COVID-19 https://doi.org/10.1148/ryai.240218 @asset25.bsky.social #ACVC2026 #Cardiology #CVRad #radiology
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Atefeh Abdomanafi, PhD on the importance of considering physical constraints in AI models for radiology radiologyai.substack.com/p/from-correlation-to-co... #ACVC2026 #Cardiology #CVRad #radiology
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Deep Learning for Coronary Stenosis Detection in Heavily Calcified Plaques at Coronary CT Angiography: A Stepwise, Multicenter Study https://doi.org/10.1148/ryai.250109 #ACVC2026 #Cardiology #CVRad #radiology
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Visualizing Radiologic Connections: An Explainable Coarse-to-Fine Foundation Model with Multiview Mammograms and Associated Reports https://doi.org/10.1148/ryai.240646 #ACVC2026 #Cardiology #CVRad #radiology
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A new deep learning model for automatic quantification of coronary luminal stenosis in patients with heavily calcified plaques on coronary CT angiography https://doi.org/10.1148/ryai.250109 #STR2026 #ChestRad #CVRad #radiology
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MRI-derived extra-axial cerebrospinal fluid (eaCSF) reference values for children and adolescents: a tool for assessing atypical eaCSF development https://doi.org/10.1148/ryai.250123 #STR2026 #ChestRad #CVRad #radiology
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How does noise from LLM-generated annotations effect AI classification performance? A new simulation study reveals systematic, prevalence-dependent biases in model evaluation. https://doi.org/10.1148/ryai.250477 #STR2026 #ChestRad #CVRad #radiology
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A self-supervised text-vision framework that can accurately detect clinically relevant brain MRI abnormalities without expert-labelled training data https://doi.org/10.1148/ryai.240619 #STR2026 #ChestRad #CVRad #radiology
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US-derived Pediatric Kidney Length and Volume Percentiles by Age: A Big Data Approach https://doi.org/10.1148/ryai.250056 #STR2026 #ChestRad #CVRad #radiology
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Deep learning–based assessment of coronary stenosis in vessels with heavily calcified plaques on coronary CT angiography https://doi.org/10.1148/ryai.250109 #STR2026 #ChestRad #CVRad #radiology
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Ontologies still matter to Radiology AI. A new post on the Vasty Deep explains why. radiologyai.substack.com/p/are-ontologies-still-r... #STR2026 #ChestRad #CVRad #radiology
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An interpretable self-supervised, abnormality-aware strategy for multiview mammogram analysis developed using in a retrospective cohort of 1626 patients https://doi.org/10.1148/ryai.240646 #STR2026 #ChestRad #CVRad #radiology
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Researchers meet in Hershey, PA to discuss the importance of human factors for AI in radiology radiologyai.substack.com/p/why-human-factors-matt... #STR2026 #ChestRad #CVRad #radiology
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Agentic AI in Radiology: Evolution from Large Language Models to Future Clinical Integration https://doi.org/10.1148/ryai.250651 #STR2026 #ChestRad #CVRad #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 #STR2026 #ChestRad #CVRad #radiology
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MRI-derived extra-axial cerebrospinal fluid (eaCSF) reference values for children and adolescents: a tool for assessing atypical eaCSF development https://doi.org/10.1148/ryai.250123 #STR2026 #ChestRad #CVRad #radiology
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How does noise from LLM-generated annotations effect AI classification performance? A new simulation study reveals systematic, prevalence-dependent biases in model evaluation. https://doi.org/10.1148/ryai.250477 #STR2026 #ChestRad #CVRad #radiology
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Why word count limits still matter in the age of digital articles radiologyai.substack.com/p/why-word-count-limits-... #STR2026 #ChestRad #CVRad #radiology
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Open-Source Dataset for the RSNA Screening Mammography Cancer Detection Challenge https://doi.org/10.1148/ryai.250375 #STR2026 #ChestRad #CVRad #radiology
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Random convolutions serve as a data augmentation strategy for deep learning-based medical image segmentation models https://doi.org/10.1148/ryai.240502 @tum.de #STR2026 #ChestRad #CVRad #radiology
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Visualizing Radiologic Connections: An Explainable Coarse-to-Fine Foundation Model with Multiview Mammograms and Associated Reports https://doi.org/10.1148/ryai.240646 #STR2026 #ChestRad #CVRad #radiology
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Toward Patient-Centered AI in Radiology radiologyai.substack.com/p/toward-patient-centere... #STR2026 #ChestRad #CVRad #radiology
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Rethinking Privacy in Medical Imaging AI: From Metadata and Pixel-level Identification Risks to Federated Learning and Synthetic Data Challenges https://doi.org/10.1148/ryai.250273 #STR2026 #ChestRad #CVRad #radiology
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Why word count limits still matter in the age of digital articles radiologyai.substack.com/p/why-word-count-limits-... #STR2026 #ChestRad #CVRad #radiology
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New mammography dataset with BI-RADS, breast density, machine ID, and outcome data freely available to the research community https://doi.org/10.1148/ryai.250375 #STR2026 #ChestRad #CVRad #radiology
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Researchers meet in Hershey, PA to discuss the importance of human factors for AI in radiology radiologyai.substack.com/p/why-human-factors-matt... #STR2026 #ChestRad #CVRad #radiology
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A retrospective study defines extra-axial cerebrospinal fluid growth charts to support diagnosis of benign enlargement of the subarachnoid space https://doi.org/10.1148/ryai.250123 #STR2026 #ChestRad #CVRad #radiology
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Leveraging free-text neuroradiology reports to develop a self-supervised text-vision framework for detecting abnormalities on brain MRI https://doi.org/10.1148/ryai.240619 #STR2026 #ChestRad #CVRad #radiology
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Self-supervised Text-vision Alignment for Automated Brain MRI Abnormality Detection: A Multicenter Study (ALIGN Study) https://doi.org/10.1148/ryai.240619 #CMR2026 #CVRad #radiology
