Patents Assigned to SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
  • Patent number: 10962661
    Abstract: Methods and systems for detecting a three-dimensional position of a scintillation event converting a radiation into a light. For example, a system includes a crystal array including a plurality of crystal elements arranged at least along a first direction and a second direction, the plurality of crystal elements extending along a third direction between a first end and a second end, the plurality of crystal elements being configured to receive the radiation entered from the second end; wherein: the plurality of crystal elements is arranged into a plurality of crystal pairs; each of the plurality of crystal pairs optically coupled to one light bridge at the first end extending and bridging light along the first direction; each of the plurality of crystal pairs is optically coupled for the light in the second direction with at least a neighboring crystal pair only through two light tunnels.
    Type: Grant
    Filed: July 31, 2019
    Date of Patent: March 30, 2021
    Assignee: Shanghai United Imaging Intelligence Co., Ltd.
    Inventors: Hongdi Li, Shaohui An
  • Publication number: 20210090736
    Abstract: The present disclosure relates to systems and methods for anomaly detection for a medical procedure. The method may include obtaining image data collected by one or more visual sensors via monitoring a medical procedure and a trained machine learning model for anomaly detection. The method may include determining a detection result for the medical procedure based on the image data using the trained machine learning model. The detection result may include whether an anomaly regarding the medical procedure exists. In response to the detection result that the anomaly exists, the method may further include providing feedback relating to the anomaly.
    Type: Application
    Filed: September 24, 2019
    Publication date: March 25, 2021
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Arun Innanje, Ziyan Wu, Abhishek Sharma, Srikrishna Karanam
  • Patent number: 10950026
    Abstract: Method and system for displaying a medical image. For example, a computer-implemented method for displaying a medical image includes acquiring an original image of a target; obtaining a lesion region in the original image; selecting a region of interest in the original image based on at least the lesion region, the region of interest including the lesion region; obtaining a plurality of planar images of the region of interest from the original image of the target based on at least a predetermined setting; generating an animated display by grouping the plurality of planar images based on at least a predetermined order; and displaying the animated display related to the region of interest including the lesion region.
    Type: Grant
    Filed: July 3, 2019
    Date of Patent: March 16, 2021
    Assignee: Shanghai United Imaging Intelligence Co., Ltd.
    Inventors: Dijia Wu, Yaozong Gao, Yiqiang Zhan
  • Publication number: 20210065413
    Abstract: A system for Magnetic Resonance Imaging (MRI) is provided. The system may obtain at least one training sample each of which includes full MRI data. The system may also obtain a preliminary subsampling model and a preliminary MRI reconstruction model. The system may further generate a subsampling model corresponding to an MRI reconstruction model by jointly training the preliminary subsampling model and the preliminary MRI reconstruction model using the at least one training sample. The subsampling model may be the trained preliminary subsampling model, and the MRI reconstruction model may be at least a portion of the trained preliminary MRI reconstruction model.
    Type: Application
    Filed: August 26, 2020
    Publication date: March 4, 2021
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Xiaoqian HUANG, Shu LIAO
  • Patent number: 10902651
    Abstract: The disclosure relates to systems and methods for magnetic resonance imaging (MRI). A method may include obtaining k-space data associated with MR signals acquired by an MR scanner. The k-space data may corresponding to a first sampling rate. The method may also include generating one or more estimated images based on the k-space data and a target neural network model. The one or more estimated images may correspond to a second sampling rate that exceeds the first sampling rate. The method may further include determining one or more target images based on the one or more estimated images and the k-space data using a compressed sensing model. The compressed sensing model may be constructed based on the one or more estimated images.
    Type: Grant
    Filed: December 28, 2018
    Date of Patent: January 26, 2021
    Assignees: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD., SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Xiaoqian Huang, Guobin Li, Nan Liu, Yang Xin
  • Patent number: 10887558
    Abstract: Methods and systems for automatically setting up a sensor connected to an apparatus. For example, a computer-implemented method for automatically setting up a sensor connected to an apparatus includes: receiving a sensor-connection signal corresponding to a connection established between the sensor and the apparatus; determining whether a streaming microservice corresponding to the sensor has been downloaded onto the apparatus; if the streaming microservice has not been downloaded onto the apparatus, determining whether the streaming microservice corresponding to the sensor is supported by the apparatus; if the streaming microservice is supported by the apparatus, downloading a streaming microservice docker from a docker registry, the streaming microservice docker including the streaming microservice and a driver corresponding to the sensor; and deploying the streaming microservice with the driver corresponding to the sensor.
    Type: Grant
    Filed: September 9, 2019
    Date of Patent: January 5, 2021
    Assignee: Shanghai United Imaging Intelligence Co., Ltd.
    Inventors: Arun Innanje, Abhishek Sharma, Ziyan Wu, Terrence Chen
  • Publication number: 20200342637
    Abstract: A system for PET image reconstruction is provided. The system may obtain PET data of a subject. The PET data may be associated with a plurality of coincidence events, which includes scattering events. The system may also generate a preliminary scatter sinogram relating to the scattering events based on the PET data. The system may also generate a target scatter sinogram relating to the scattering events by applying a scatter sinogram generator based on the preliminary scatter sinogram. The target scatter sinogram may have a higher image quality than the preliminary scatter sinogram. The system may further reconstruct a target PET image of the subject based on the PET data and the target scatter sinogram.
    Type: Application
    Filed: April 27, 2020
    Publication date: October 29, 2020
    Applicants: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD., SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.
    Inventors: Yang ZHANG, Shu LIAO, Liuchun HE, Zilin DENG
  • Publication number: 20200272841
    Abstract: A system for image segmentation is provided. The system may obtain a target image including an ROI, and segment a preliminary region representative of the ROI from the target image using a first ROI segmentation model corresponding to a first image resolution. The system may segment a target region representative of the ROI from the preliminary region using a second ROI segmentation model corresponding to a second image resolution. At least one model of the first and second ROI segmentation models may at least include a first convolutional layer and a second convolutional layer downstream to the first convolutional layer. A count of input channels of the first convolutional layer may be greater than a count of output channels of the first convolutional layer, and a count of input channels of the second convolutional layer may be smaller than a count of output channels of the second convolutional layer.
    Type: Application
    Filed: May 9, 2020
    Publication date: August 27, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Miaofei HAN, Yu ZHANG, Yaozong GAO, Yiqiang ZHAN
  • Publication number: 20200205766
    Abstract: A method for exposure controlling in medical device may include obtaining one or more exposure parameters relating to an exposure process associated with an object performed by a radiation device. The method may also include obtaining object information relating to the object. The method may also include determining an exposure moment based on the object information. The method may also include causing the radiation device to perform the exposure process to the object based on the one or more exposure parameters and the exposure moment.
    Type: Application
    Filed: December 29, 2019
    Publication date: July 2, 2020
    Applicants: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD., SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.
    Inventors: Dijia WU, Yongqin XIAO
  • Publication number: 20200211160
    Abstract: The present disclosure provides a system for image reconstruction. The system may obtain an initial image of a subject. The initial image may be generated based on scan data of the subject that is collected by an imaging device. The system may also generate a gradient image associated with the initial image. The system may further generate a target image of the subject by applying an image reconstruction model based on the initial image and the gradient image. The target image may have a higher image quality than the initial image.
    Type: Application
    Filed: December 26, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Yang ZHANG, Yang LYU, Chen XI
  • Publication number: 20200209109
    Abstract: A system for fault diagnosis is provided. The system may acquire a vibration signal of a target device, and determine one or more feature values of the vibration signal. The system may further determine a fault condition of the target device by applying a fault diagnosis model to the feature values. The fault diagnosis model may include a trained first component including a plurality of stacked trained RBMs, and a trained second component connected to the trained first component. The trained second component may include a trained fully connected layer and a trained output layer connected to the trained fully connected layer.
    Type: Application
    Filed: December 27, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Xinran LIANG, Xiang Sean ZHOU
  • Publication number: 20200211188
    Abstract: The present disclosure provides systems and methods for image processing. The method may include obtaining an initial image; obtaining an intermediate image corresponding to the initial image, the intermediate image including pixels or voxels associated with at least a portion of a target object in the initial image; obtaining a trained processing model; and generating, based on the initial image and the intermediate image, a target image associated with the target object using the trained processing model.
    Type: Application
    Filed: December 28, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Yaozong GAO, Wenhai ZHANG, Yiqiang ZHAN
  • Publication number: 20200211186
    Abstract: The present disclosure may provide a method. The method may include processing an image of a subject using a detection model to generate one or more detection results corresponding to one or more objects in the image; and generating an image metric of the image based on the one or more detection results corresponding to the one or more objects.
    Type: Application
    Filed: December 27, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Zaiwen GONG, Hengze ZHAN, Jie-Zhi CHENG, Yiqiang ZHAN, Jibing WU, Xiang Sean ZHOU
  • Publication number: 20200211209
    Abstract: The present disclosure is related to systems and methods for image processing. The method includes obtaining a first image of a first modality. The method includes generating a second image of a second modality by processing, based on a trained machine learning model, the first image. The second modality may be different from the first modality.
    Type: Application
    Filed: December 28, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Shu LIAO, Yunhao GE, Dongming WEI
  • Publication number: 20200211236
    Abstract: System for image correction in PET is provided. The system may acquire a PET image and a CT image of a subject. The system may generate, based on the PET image and the CT image, an attenuation-corrected PET image of the subject by application of an attenuation correction model. The attenuation correction model may be a trained cascaded neural network including a trained first model and at least one trained second model downstream to the trained first model. During the application of the attenuation correction model, an input of each of the at least one trained second model may include the PET image, the CT image, and an output image of a previous trained model that is upstream and connected to the trained second model.
    Type: Application
    Filed: December 27, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Yang ZHANG, Yang LYU, Chen XI
  • Publication number: 20200210761
    Abstract: The present disclosure provides a system and method for classification determination of a structure. The method may include obtaining image data representing a structure of a subject. The method may also include determining a plurality of candidate classifications of the structure and their respective probabilities by inputting the image data into a classification model. The classification model may include a backbone network for determining a backbone feature of the structure, a segmentation network for determining a segmentation feature of the structure, and a density classification network for determining a density feature of the structure. The method may further include determining a target classification of the structure based on at least a part of the probabilities of the plurality of candidate classifications.
    Type: Application
    Filed: December 27, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Yanbo CHEN, Yaozong GAO, Yiqiang ZHAN
  • Publication number: 20200211187
    Abstract: Systems and methods for ossification center detection (OCD) and bone age assessment (BAA) may be provided. The method may include obtaining a bone age image of a subject. The method may include generating a normalized bone age image by preprocessing the bone age image. The method may include determining, based on the normalized bone age image, positions of a plurality of ossification centers using an ossification center localization (OCL) model. The method may include estimating, based on the normalized bone age image and information related to the positions of the plurality of ossification centers, a bone age of the subject using a bone age assessment (BAA) model.
    Type: Application
    Filed: December 28, 2019
    Publication date: July 2, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Minqing ZHANG, Qin LIU, Dijia WU, Yiqiang ZHAN, Xiang Sean ZHOU
  • Publication number: 20200167586
    Abstract: The present disclosure provides a region of interest (ROI) detection system. The system may be configured to acquire a target image and an ROI detection model, and perform ROI detection on the target image by applying the ROI detection model to the target image. The ROI detection model may be a trained cascaded neural network including a plurality of sequentially connected trained models. The plurality of trained models may include a trained first model and at least one trained second model downstream to the trained first model in the trained cascaded neural network. The plurality of trained models may be sequentially trained. Each of the trained second model may be trained using a plurality of training samples determined based on one or more trained models of the plurality of trained models generated before the generation of the trained second model.
    Type: Application
    Filed: October 14, 2019
    Publication date: May 28, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Yaozong GAO, Yanbo CHEN, Jiyong WANG, Weiyang XIE, Yiqiang ZHAN
  • Publication number: 20200098108
    Abstract: A method for assessing a condition of an organ or tissue of a target object is provided. The method may include: obtaining a target image of the target object; segmenting a target region from the target image, the target region of the target image corresponding to a sub-region of the organ or tissue; determining a morphological characteristic value of the target region in the target image; obtaining a reference standard associated with a sample organ or tissue of a plurality of sample objects, the sample organ or tissue being of a same type as the organ or tissue of the target object; and assessing the condition of the organ or tissue of the target object by comparing the morphological characteristic value of the target region in the target image with the reference standard.
    Type: Application
    Filed: September 19, 2019
    Publication date: March 26, 2020
    Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.
    Inventors: Quan HUO, Feng SHI, Qingfeng LI, Bokai LI, Yiqiang ZHAN
  • Publication number: 20200090382
    Abstract: The disclosure relates to systems and methods for magnetic resonance imaging (MRI). A method may include obtaining k-space data associated with MR signals acquired by an MR scanner. The k-space data may corresponding to a first sampling rate. The method may also include generating one or more estimated images based on the k-space data and a target neural network model. The one or more estimated images may correspond to a second sampling rate that exceeds the first sampling rate. The method may further include determining one or more target images based on the one or more estimated images and the k-space data using a compressed sensing model. The compressed sensing model may be constructed based on the one or more estimated images.
    Type: Application
    Filed: December 28, 2018
    Publication date: March 19, 2020
    Applicants: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD., SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.
    Inventors: Xiaoqian HUANG, Guobin LI, Nan LIU, Yang XIN