Tyche: Stochastic In-Context Learning for Medical Image Segmentation

Understand

Existing learning-based solutions to medical image segmentation have two important shortcomings.

• First, for most new segmentation task, a new model has to be trained or fine-tuned.
• This requires extensive resources and machine learning expertise, and is therefore often infeasible for medical researchers and clinicians.
• Second, most existing segmentation methods produce a single deterministic segmentation mask for a given image.