A “scientific sandbox” lets researchers explore the evolution of vision systems
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
Acting as a “virtual spectrometer,” SpectroGen generates spectroscopic data in any modality, such as X-ray or infrared, to quickly assess a material’s quality.
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
MIT CSAIL researchers developed a tool that can model the shape and movements of fetuses in 3D, potentially assisting doctors in finding abnormalities and making diagnoses.
A new method helps convey uncertainty more precisely, which could give researchers and medical clinicians better information to make decisions.
The framework helps clinicians choose phrases that more accurately reflect the likelihood that certain conditions are present in X-rays.
The method could help communities visualize and prepare for approaching storms.
New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.
“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.