- Billerica MA, US Eugene BZOWEJ - Reading MA, US Kenneth R. CROUNSE - Somerville MA, US John L. MARSHALL - Sedgwick ME, US Brandon MACDONALD - Melrose MA, US Ziyan WU - Wayland MA, US Lee YEZEK - Watertown MA, US
International Classification:
G02F 1/00 G09G 3/34
Abstract:
An electrophoretic medium includes a fluid, a plurality of light scattering charged particles having a first polarity, and a first, second, and third set of particles, each set having a color different from each other set. The first and second particles may have a second polarity opposite to the first polarity, and the mobility of the third set of particles is less than half of the mobility of the light scattering particles, the first set of charged particles, and the second set of charged particles.
Systems And Methods For Automated Healthcare Services
Healthcare services can be automated utilizing a system that recognizes at least one characteristic of a patient based on images of the patient acquired by an image capturing device. Relying on information extracted from these images, the system may automate multiple aspects of a medical procedure such as patient identification and verification, positioning, diagnosis and/or treatment planning using artificial intelligence or machine learning techniques. By automating these operations, healthcare services can be provided remotely and/or with minimum physical contact between the patient and a medical professional.
Key Points Detection Using Multiple Image Modalities
- Shanghai, CN Arun Innanje - Lexington MA, US Ziyan Wu - Lexington MA, US
Assignee:
Shanghai United Imaging Intelligence Co., Ltd. - Shanghai
International Classification:
G06T 7/73 G06T 7/00 G06N 3/04 G06K 9/00
Abstract:
Image-based key points detection using a convolutional neural network (CNN) may be impacted if the key points are occluded in the image. Images obtained from additional imaging modalities such as depth and/or thermal images may be used in conjunction with RGB images to reduce or minimize the impact of the occlusion. The additional images may be used to determine adjustment values that are then applied to the weights of the CNN so that the convolution operations may be performed in a modality aware manner to increase the robustness, accuracy, and efficiency of key point detection.
A method of expanding a visual learning database in a computer by teaching the computer includes providing a series of training images to the computer wherein each series includes three images with each image falling within a unique image domain and with each image domain representing a possible combination of a first attribute and a second attribute with a first image domain including the first attribute and the second attribute in a first state (X=0, Y=0), a second image domain including the first attribute in a second state and the second attribute in the first state (X=1, Y=0), and a third image domain including the first attribute in the first state and the second attribute in the second state (X=0, Y=1). The method also includes developing within the computer forward generators and reverse generators between the first image domain, the second image domain, the third image domain, and a fourth image domain for which no training image is provided, and applying with the computer the forward generators and reverse generators to single images that fall within one of the first image domain, the second image domain, the third image domain, and a fourth image domain to generate images for the remaining domains to populate a database.
- Shangha, CN Ziyan Wu - Cambridge MA, US Terrence Chen - Cambridge MA, US
Assignee:
Shanghai United Imaging Intelligence Co., LTD. - Shangha
International Classification:
A61B 6/00 G06N 3/08 G06N 3/04 G06K 9/62
Abstract:
An apparatus is configured to receive input image data corresponding to output image data of a first radiology scanner device, translate the input image data into a format corresponding to output image data of a second radiology scanner device and generate an output image corresponding to the translated input image data on a post processing imaging device associated with the first radiology scanner device. Medical images from a new scanner can be translate to look as if they came from a scanner of another vendor.
- München, DE Ziyan Wu - Lexington MA, US Jan Ernst - Princeton NJ, US
International Classification:
G06T 7/73 G06T 7/11
Abstract:
Systems, methods, and computer-readable media are described for determining the orientation of a target object in an image and iteratively reorienting the target object until an orientation of the target object is within an acceptable threshold of a target orientation. Also described herein are systems, methods, and computer-readable media for verifying that an image contains a target object.
SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD. - Shanghai
International Classification:
A61B 5/00 A61B 5/11 A61B 5/113
Abstract:
A method for medical imaging is provided. The method may include automatically determining that a positioning procedure of a subject has been finished based on image data of the subject captured by an image capturing device. The method may also include obtaining status information of a medical device. The method may further include causing the medical device to perform a scan on the subject based on a determination result that the positioning procedure of the subject has been finished, the status information of the medical device, and a starting signal of the scan.
System And Methods For Privacy Preserving Cross-Site Federated Learning
- Shanghai, CN Ziyan Wu - Cambridge MA, US Abhishek Sharma - Cambridge MA, US Arun Innanje - Cambridge MA, US Terrence Chen - Cambridge MA, US
Assignee:
Shanghai United Imaging Intelligence Co., LTD. - Shanghai
International Classification:
G06N 20/00 H04L 29/06
Abstract:
Data samples are transmitted from a central server to at least one local server apparatus. The central server receives a set of predictions from the at least one local server apparatus that are based on the transmitted set of data samples. The central server trains a central model based on the received set of predictions. The central model, or a portion of the central model corresponding to a task of interest, can then be sent to the at least one local server apparatus. Neither local data from local sites nor trained models from the local sites are transmitted to the central server. This ensures protection and security of data at the local sites.
Mar 2009 to Jul 2009 System EngineerHoneywell Technology Solution Labs
Jun 2008 to Aug 2008 Intern, Security and Building SolutionsIntel
Sep 2006 to Nov 2006 Intern, High Performance ComputingNational Instruments
Jun 2005 to Aug 2005 InternSun Yet-Sen University and Guangzhou Metrology Satellites Station Guangzhou, CN Jun 2002 to 2003 Intern
Education:
Rensselaer Polytechnic Institute Troy, NY 2013 Ph.D. in Computer and Systems EngineeringBeijing University of Aeronautics 2006 to 2009 M.S. in Machine Vision and InspectionBeijing University of Aeronautics and Astronautics 2002 to 2006 B.S. in Electrical Engineering and Automation