General Electric Company

Ge Precision Healthcare LLC

Bo Wang

Thomas Kwok-Fah Foo

Jhimli Mitra

Nicholas Joseph Kray

Lowell Scott Smith

Huan Tan

Ian Francis Prentice

Scott Roger Finn

David Martin Mills

Li Zhang

Warren Lee

Desmond Teck Beng Yeo

Yakov Polishchuk

Dong-Jin Shim

Bryan P Bednarz

Roberta Marie Strigel

Pranav Dhoj Shah

James Hartman Holmes

A system including at least three robots. Each robot including a proximity sensor unit and an imaging device. At least one robot including a processor to perform a method of estimating a pose of a human, the method including obtaining a first pose estimate for the human, the first pose estimate based on proximity sensor information, obtaining a second pose estimate for the human, the second pose estimate based on imaging device information, and generating a refined pose estimate for the human by fusing the first pose estimate with the second pose estimate, where the first pose information provides predictive values and the second pose estimate provides correction values. The method including applying a deep neural network (DNN) human model, and applying a DNN human pose model. A method to generate a refined pose estimation for a human and a non-transitory computer readable medium are also disclosed.

Systems and methods for locating humans using dynamic field robotic-sensor network of human robot team

A system and method for providing virtual real-time MRI-guidance for a biopsy outside of a conventional MRI scanner is described. MR images and ultrasound images of a region of a patient's body are simultaneously acquired during a pre-biopsy procedure. Respiratory states that the patient may experience during the biopsy are then determined from the acquired ultrasound images, and each respiratory state is associated with corresponding MR images. The MR images are indexed with their corresponding respiratory state. Ultrasound images are then acquired of the patient during a biopsy procedure. The respiratory state of the patient is determined from the ultrasound images, and the corresponding indexed MR images are displayed.

Image-guided biopsy techniques

A method is provided. The method includes acquiring simultaneously multiple magnetic resonance (MR) images and multiple ultrasound images of an anatomical region of a subject over a scanned duration. The method also includes training an unsupervised deep learning-based deformable registration network. This training includes training a MR registration subnetwork based on the multiple MR images to generate MR deformation and transformation vectors, training an ultrasound registration subnetwork based on the multiple ultrasound images to generate ultrasound deformation and transformation vectors, and training a MR-to-ultrasound subnetwork based the multiple MR images and the multiple ultrasound images to generate MR-to-ultrasound deformation and transformation vectors between corresponding pairs of MR images and ultrasound images at each time point.

System and method for unsupervised deep learning for deformable image registration

An airfoil, a fan assembly and an engine include at least one airfoil including a root portion, a body portion and a tip portion. The body portion is configured extending radially outward from the root portion and the tip portion is configured extending radially outward from the root portion and the body portion. The airfoil including a suction and a pressure side coupled together at a leading and a trailing edge and extending therebetween. The airfoil including a compliant tip at the tip portion. The compliant tip extending along at least a portion of the tip portion in a chord-wise direction and a span-wise direction. The compliant tip is configured to provide wave propagation along the tip portion such that critical strain proximate the tip portion and the trailing edge is reduced during a foreign object impact.

Airfoils including compliant tip

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Schenectady, NY, United States of America

Bo Wang