1 citations · 1 across the 3 of their papers we have counts for
3 papers
MHub.ai: A Simple, Standardized, and Reproducible Platform for AI Models in Medical Imaging
Leonard Nürnberg, Dennis Bontempi, Suraj Pai +17
Artificial intelligence (AI) has the potential to transform medical imaging by automating image analysis and accelerating clinical research. However, research and clinical use are…
Clinical Validation and Prospective Deployment of an Automated Deep Learning-Based Coronary Segmentation and Cardiac Toxicity Risk Prediction System
Christian V. Guthier, Christopher E Kehayias, Cosmin Ciausu +15
Importance: Coronary algorithm for cardiac sub structures and prospective real-time surveillance of cardiac dose exposure. Methods: Retro and prospective study to validate AI auto-…
Benchmarking of Deep Learning Methods for Generic MRI Multi-Organ Abdominal Segmentation
Deepa Krishnaswamy, Cosmin Ciausu, Steve Pieper +3
Recent advances in deep learning have led to robust automated tools for segmentation of abdominal computed tomography (CT). Meanwhile, segmentation of magnetic resonance imaging (M…