Dignity Health

Arizona State University

Other

Carl Zeiss Meditec Ag

Mark C Preul

Evgenii Belykh

David Naughton

Mohammadhassan Izadyyazdanabadi

Lena Mary Houlihan

Christoph Hauger

Peter Nakaji

Robert F Spetzler

Merrill J Birdno

Peter Maxwell Delaney

Yezhou Yang

Guido Hattendorf

Brent Vernon

Jennifer Eschbacher

Various embodiments of a system and associated method for modeling an average surgical corridor based on a plurality of datasets are disclosed herein.

Systems and methods for a spatial quantitative and anatomically accurate surgical corridor modeling platform

Various embodiments of a system and associated method for determining a volume of surgical freedom using a plurality of three-dimensional extrema points along a surgical corridor in relation to a structure of interest are disclosed herein.

Systems and methods for volumetric measurement of maximal allowable working volume within a surgical corridor

In accordance with some embodiments of the disclosed subject matter, systems, methods, and media for selectively presenting images captured by confocal laser endomicroscopy (CLE) are provided. In some embodiments, a method comprises: receiving images captured by a CLE device during brain surgery; providing the images to a convolution neural network (CNN) trained using at least a plurality of images of brain tissue captured by a CLE device and labeled diagnostic or non-diagnostic; receiving an indication, from the CNN, likelihoods that the images are diagnostic images; determining, based on the likelihoods, which of the images are diagnostic images; and in response to determining that an image is a diagnostic image, causing the image to be presented during the brain surgery.

Systems, methods, and media for selectively presenting images captured by confocal laser endomicroscopy

In accordance with some embodiments of the disclosed subject matter, systems, methods, and media for automatically transforming a digital image into a simulated pathology image are provided. In some embodiments, the method comprises: receiving a content image from an endomicroscopy device; receiving, from a hidden layer of a convolutional neural network (CNN) trained to recognize a multitude of classes of common objects, features indicative of content of the content image; receiving, providing a style reference image to the CNN; receiving, from another hidden layer of the CNN, features indicative of a style of the style reference image; receiving, from the hidden layers of the CNN, features indicative of content and style of a target image; generating a loss value based on the features of the content image, the style reference image, and the target image; minimizing the loss value; and displaying the target image with the minimized loss.

Systems, methods, and media for automatically transforming a digital image into a simulated pathology image

A method of detecting a brain tumor includes administering indocyanine green to a living body; exposing brain tissue in the living body; irradiating the exposed brain tissue with excitation light of indocyanine green; obtaining an image based on fluorescence of the excited indocyanine green in the brain tissue, wherein the image is obtained using an endomicroscope; and identifying portions of the brain tissue corresponding to the brain tumor based on the image.

Surgical optical systems for detecting brain tumors

A method and composition for treating arteriovenous malformations (AVMs), or abnormal vasculature in the body are provided. The method comprises introducing into the region of an AVM a composition comprising a nucleophilic component, such as a thiol, and a component containing a conjugated unsaturated bond, such as an acrylate through a catheter, whereby the composition crosslinks within the body to block or occlude the AVM.

In situ gelling self-reactive materials for embolization

Growing community of inventors

Scottsdale, AZ, United States of America

Mark C Preul