AI in medical imaging

ElastoNet: A revolutionary neural network approach to MR Elastography inversion with uncertainty quantification.

ElastoNet 1: The Revolutionary Neural Network for MRE Wave Inversion with Uncertainty Quantification (Pros & Cons)

Medical imaging has seen a rapid evolution over the past decade, especially in non-invasive diagnostics. Among these advancements, Magnetic Resonance Elastography (MRE) has emerged as a powerful technique for evaluating tissue stiffness — a key biomarker in diagnosing diseases like…

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How Adaptive Multi-Teacher Knowledge Distillation Enables Lightweight Medical Segmentation with Limited Site Data.

How Adaptive Multi-Teacher Knowledge Distillation Enables Lightweight Medical Segmentation with Limited Site Data

A model trained to segment the prostate in MRI scans from one institution routinely fails when presented with scans from another hospital that uses a different scanner, a different field strength, or a different slice thickness. This is not a…

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