Cornell University

Memorial Sloan Kettering Cancer Center

Krishna Juluru

Michelle S Bradbury

Henning U Voss

Douglas J Ballon

Brittany Dashevsky

Eric Aronowitz

Presented herein are systems, methods, and architectures related to augmented reality (AR) surgical visualization of one or more dual-modality probe species in tissue. As described herein, near infrared (NIR) images are detected and rendered in real time. The NIR images are registered and/or overlaid with one or more radiological images (e.g., which were obtained preoperatively/perioperatively) by a processor [e.g., that uses an artificial neural network (ANN) or convolutional neural network (CNN) reconstruction algorithm] to produce a real-time AR overlay (3D representation). The AR overlay is displayed to a surgeon in real time. Additionally, a dynamic motion tracker tracks the location of fiducial tracking sensors on/in/about the subject, and this information is also used by the processor in producing (e.g., positionally adjusting) the AR overlay. The real-time AR overlay can improve surgery outcomes, for example, by providing additional real-time information about a surgical site via an intuitive visual interface.

Systems for augmented reality surgical and clinical visualization

The present disclosure discusses systems and methods for imaging tissue. The system can reduce the amount of vibrations that are transmitted from a magnetic resonance imaging device to a tissue sample. The system can include a stabilization platform with at least one vibration dampener coupled towards either end of the stabilization platform. A fluid reservoir is coupled to the stabilization platform and a resonator is coupled to the exterior of the fluid reservoir.

Systems and methods for MR microscopy analysis of resected tissue

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New York, NY, United States of America

Krishna Juluru