Giouroukou et al. review imaging data preparation for AI use: methods for protecting patient privacy https://doi.org/10.1148/ryai.250273 #FederatedLearning #deidentification #ML

New data resource with 4-view 2D mammograms and corresponding BI-RADS assessment, breast density, machine ID, and proof of benign or malignant outcome https://doi.org/10.1148/ryai.250375 #mammo #mammogram #AI

In new Kaggle challenge, SPR asks researchers to predict BI-RADS from mammography reports https://radiologyai.substack.com/p/spr-launches-a-new-kaggle-challenge #breastcancer #innovation #MachineLearning

Meet the people leading the science and use of #AI in radiology! Check out our #podcast series on Apple Podcasts, Google Play, or Spotify https://rsnaradiologyai.libsyn.com/#AI#podcast#MachineLearning #DeepLearning #ArtificialIntelligence

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 #LLM #LargeLanguageModels #AI

Self-supervised Text-vision Alignment for Automated Brain MRI Abnormality Detection: A Multicenter Study (ALIGN Study) https://doi.org/10.1148/ryai.240619 #brain #DeepLearning #MachineLearning

Even in the age of digital articles, conciseness matters https://radiologyai.substack.com/p/why-word-count-limits-still-matter #sciencewriting #AI #ML

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 #NeuroRad #MRI #AI

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 #HeartDz #cardiology #ML

A natural language processing model extracts normal kidney length and volume percentiles for pediatric patients from a large US dataset https://doi.org/10.1148/ryai.250056 #kidney #AI #MachineLearning

Sign up online! Get e-mail alerts for The Vasty Deep, the @radiology-ai.bsky.social editor's blog https://radiologyai.substack.com/ #AI #MachineLearning #DeepLearning

Body Charts from CT Segmentations across the Adult Lifespan: Large-scale Cross-sectional and Longitudinal Analyses https://doi.org/10.1148/ryai.250506 #segmentation #ChestRad #Liver

A new narrative review describes the evolution of AI applications for radiology from LLMs to autonomous agents https://doi.org/10.1148/ryai.250651 #CMVIT2026 #ComputerVision #AI

A new foundation model for digital mammography that extracts key information from images and reports in label-limited settings https://doi.org/10.1148/ryai.240646 #MachineLearning #mammogram #ML

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 #segmentation #ML #MachineLearning

SPR launches a new Kaggle challenge: predicting BI-RADS from mammography reports https://radiologyai.substack.com/p/spr-launches-a-new-kaggle-challenge #breastcancer #AI #ML

Deep learning–based assessment of coronary stenosis in vessels with heavily calcified plaques on coronary CT angiography https://doi.org/10.1148/ryai.250109 #HeartDisease #cardiology #ML

The Checklist for AI in Medical Imaging addresses #AI applications that include classification, segmentation, and reconstruction of medical images https://rsna.org/claim#AI#DeepLearning #Radiomics #ArtificialIntelligence

A natural language processing model extracts normal kidney length and volume percentiles for pediatric patients from a large US dataset https://doi.org/10.1148/ryai.250056 #PedsRad #AI #ML

Self-supervised Text-vision Alignment for Automated Brain MRI Abnormality Detection: A Multicenter Study (ALIGN Study) https://doi.org/10.1148/ryai.240619 #NeuroRad #AI #MachineLearning

A new foundation model for digital mammography that extracts key information from images and reports in label-limited settings https://doi.org/10.1148/ryai.240646 #ASSR26 #NeuroRad #MSKRad #radiology

Agentic AI in Radiology: Evolution from Large Language Models to Future Clinical Integration https://doi.org/10.1148/ryai.250651 #CMVIT2026 #ComputerVision #AI

From RSNA to SPR, Kaggle challenges promote AI innovation https://radiologyai.substack.com/p/spr-launches-a-new-kaggle-challenge #ASSR26 #NeuroRad #MSKRad #radiology

Random Convolutions for Domain Generalization of Deep Learning-based Medical Image Segmentation Models https://doi.org/10.1148/ryai.240502 @tum.de #ASSR26 #NeuroRad #MSKRad #radiology

Data Resources articles describe important datasets, algorithms, and standards made available to the #AI community https://pubs.rsna.org/page/ai/data_resources#AI#DeepLearning #Radiomics #ArtificialIntelligence

US-derived Pediatric Kidney Length and Volume Percentiles by Age: A Big Data Approach https://doi.org/10.1148/ryai.250056 #ASSR26 #NeuroRad #MSKRad #radiology

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 #ASSR26 #NeuroRad #MSKRad #radiology

Why word count limits still matter in the age of digital articles https://radiologyai.substack.com/p/why-word-count-limits-still-matter #ASSR26 #NeuroRad #MSKRad #radiology

Normative Trajectories of Extra-Axial Cerebrospinal Fluid during Childhood and Adolescence Defined in a Clinically Acquired MRI Dataset https://doi.org/10.1148/ryai.250123 #ASSR26 #NeuroRad #MSKRad #radiology

In new Kaggle challenge, SPR asks researchers to predict BI-RADS from mammography reports https://radiologyai.substack.com/p/spr-launches-a-new-kaggle-challenge #ASSR26 #NeuroRad #MSKRad #radiology

A retrospective study of 127,114 patients establishes reference charts for CT-derived, whole-body anatomic volumes https://doi.org/10.1148/ryai.250506 #ASSR26 #NeuroRad #MSKRad #radiology

Check out today's #FreeFriday @radiology-ai.bsky.social article from #PubMedCentral! SCIseg: Automatic Segmentation of Intramedullary Lesions in Spinal Cord Injury on T2-weighted MRI Scans https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791505#FreeFriday#PubMedCentral!#ML #MachineLearning #ArtificialIntelligence

Open-Source Dataset for the RSNA Screening Mammography Cancer Detection Challenge https://doi.org/10.1148/ryai.250375 #CMVIT2026 #ComputerVision #AI

Visualizing Radiologic Connections: An Explainable Coarse-to-Fine Foundation Model with Multiview Mammograms and Associated Reports https://doi.org/10.1148/ryai.240646 #ASSR26 #NeuroRad #MSKRad #radiology

Deep learning–based assessment of coronary stenosis in vessels with heavily calcified plaques on coronary CT angiography https://doi.org/10.1148/ryai.250109 #ASSR26 #NeuroRad #MSKRad #radiology

Random Convolutions for Domain Generalization of Deep Learning-based Medical Image Segmentation Models https://doi.org/10.1148/ryai.240502 @tum.de #ASSR26 #NeuroRad #MSKRad #radiology

From RSNA to SPR, Kaggle challenges promote AI innovation https://radiologyai.substack.com/p/spr-launches-a-new-kaggle-challenge #ASSR26 #NeuroRad #MSKRad #radiology

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 #ASSR26 #NeuroRad #MSKRad #radiology

#ThrowbackThursday – @BrdKhsrv @PRouzrokh discuss a new approach to automated bone segmentation (Mar 2025) https://doi.org/10.1148/ryai.250057#ThrowbackThursday#ML #Radiomics #ArtificialIntelligence

Are Ontologies Still Relevant in the Modern Era of AI? ... Yes! https://radiologyai.substack.com/p/are-ontologies-still-relevant-in #ASSR26 #NeuroRad #MSKRad #radiology

Agentic AI in Radiology: Evolution from Large Language Models to Future Clinical Integration https://doi.org/10.1148/ryai.250651 #ASSR26 #NeuroRad #MSKRad #radiology

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 #ASSR26 #NeuroRad #MSKRad #radiology

Maddy Cappelloni discusses the value of word counts limits in new blog post https://radiologyai.substack.com/p/why-word-count-limits-still-matter #ASSR26 #NeuroRad #MSKRad #radiology

From RSNA to SPR, Kaggle challenges promote AI innovation https://radiologyai.substack.com/p/spr-launches-a-new-kaggle-challenge #ASSR26 #NeuroRad #MSKRad #radiology

Researchers meet in Hershey, PA to discuss the importance of human factors for AI in radiology https://radiologyai.substack.com/p/why-human-factors-matter-in-ai #STR2026 #ChestRad #CVRad #radiology

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

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 #ASSR26 #NeuroRad #MSKRad #radiology

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 #ASSR26 #NeuroRad #MSKRad #radiology

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

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