Research scientists in Switzerland have developed and tested a robust AI model that automatically segments major anatomic structures in MRI images, independent of sequence, according to a study ...

Research scientists in Switzerland have developed and tested a robust AI model that automatically segments major anatomic structures in MRI images, independent of sequence. In the study, the model ...

Traditional segmentation networks treat anatomical structures as isolated elements, often neglecting their hierarchical relationships. This study introduces Softmax for Arbitrary Label Trees (SALT), a ...

Research scientists in Switzerland have developed and tested a robust AI model that automatically segments major anatomic structures in MRI images, independent of sequence, according to a new study ...

Radiologists have long had the capability to scan entire bodies. But identifying all the body's many internal structures is much harder. Now an AI system can do it instead. Whole body imaging is a ...

Deep learning-based image analysis offers great potential in clinical practice. However, it faces mainly two challenges: scarcity of large-scale annotated clinical data for training and susceptibility ...

Example MRI scans in the training dataset. Since images were randomly sampled from clinical routine, the dataset (n = 561) contains a wide variety of different contrasts, pathologies, and image types.