BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once

Understand

Biomedical image analysis is fundamental for biomedical discovery in cell biology, pathology, radiology, and many other biomedical domains.

• Holistic image analysis comprises interdependent subtasks such as segmentation, detection, and recognition of relevant objects.
• Here, we propose BiomedParse, a biomedical foundation model for imaging parsing that can jointly conduct segmentation, detection, and recognition for 82 object types across 9 imaging modalities.
• Through joint learning, we can improve accuracy for individual tasks and enable novel applications such as segmenting all relevant objects in an image through a text prompt, rather than requiring users to laboriously specify the bounding box for each object.