Patents by Inventor Yiqiang Zhan

Yiqiang Zhan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10820837
    Abstract: In a method for alpha angle measurements of a bone joint based on magnetic resonance imaging (MRI) data of the bone joint, a three-dimensional (3D) bone surface image of the bone joint is generated based on two-dimensional (2D) segmentations on radial plane slices of the bone joint. Based on the 3D bone surface image, a head center of a head of the bone joint and a neck axis of a neck of the bone joint are estimated. An alpha angle model is constructed based on the estimated head center and neck axis. Further, the alpha angle measurement is determined for each of the radial plane slices of the bone joint based on the constructed alpha angle model.
    Type: Grant
    Filed: April 9, 2019
    Date of Patent: November 3, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Liang Zhao, Esther Raithel, Yiqiang Zhan
  • Patent number: 10803354
    Abstract: A framework for cross-modality image synthesis. A first and second model may be trained using respective first and second pairs of complementary images and corresponding first and second ground truth images that represent first and second views of a region of interest. The first and second pairs of complementary images may be acquired by a first modality and the first and second ground truth images may be acquired by a second modality. A combinational network may further be trained to combine features from the first and second models. At least one synthetic second modality image may then be generated by passing current images through the trained first or second model and the combinational network, wherein the current images are acquired by the first modality and represent the first or second view of the region of interest.
    Type: Grant
    Filed: January 28, 2019
    Date of Patent: October 13, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Yu Zhao, Yimo Gao, Shu Liao, Liang Zhao, Zhennan Yan, Yiqiang Zhan, Xiang Sean Zhou
  • Publication number: 20200273160
    Abstract: Method and system for displaying one or more regions of interest of an original image. For example, a computer-implemented method for displaying one or more regions of interest of an original image includes: obtaining one or more detection results of one or more first regions of interest, each detection result of the one or more detection results corresponding to one first region of interest of the one or more first regions of interest, each detection result including image information and one or more attribute parameters for their corresponding first region of interest; and obtaining one or more attribute parameter thresholds provided by a user in real time, each attribute parameter threshold of the one or more attribute parameter thresholds corresponding to one attribute parameter of the one or more attribute parameters.
    Type: Application
    Filed: May 23, 2019
    Publication date: August 27, 2020
    Inventors: JIANFENG ZHANG, YANLI SONG, DIJIA WU, YIQIANG ZHAN, XIANG SEAN ZHOU
  • 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: 20200273162
    Abstract: Method and system for grading a tumor. For example, a system for grading a tumor comprising: an image obtaining module configured to obtain a pathological image of a tissue to be examined; a snippet obtaining module configured to obtain one or more snippets having one or more sizes from the pathological image; an analyzing module configured to obtain one or more classification features based on at least analyzing the one or more snippets using one or more selected trained detection models of the analyzing module, wherein each selected trained detection model is configured to identify one or more classification features; and an outputting module configured to determine a tumor identification result based on at least the one or more classification features and output the tumor identification result.
    Type: Application
    Filed: October 18, 2019
    Publication date: August 27, 2020
    Inventors: QIUPING CHUN, Feng Shi, 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: 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: 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: 20200211695
    Abstract: Method and system for grading a medical image. For example, a system for grading a medical image comprising a grading network configured to provide a grading result corresponding to the medical image based on at least the medical image and/or a list of lesion candidates generated by a lesion identification network.
    Type: Application
    Filed: July 12, 2019
    Publication date: July 2, 2020
    Inventors: JIEZHI ZHENG, ZAIWEN GONG, ZHIQIANG HE, YIQIANG ZHAN, XIANG SEAN ZHOU
  • 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
  • Patent number: 10685438
    Abstract: A framework for automated measurement. In accordance with one aspect, the framework detects a centerline point of a structure of interest in an image. A centerline of the structure of interest may be traced based on the detected centerline point. A trained segmentation learning structure may be used to generate one or more contours of the structure of interest along the centerline. One or more measurements may then be extracted from the one or more contours.
    Type: Grant
    Filed: June 25, 2018
    Date of Patent: June 16, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Fitsum Aklilu Reda, Yiqiang Zhan, Parmeet Singh Bhatia, Yoshihisa Shinagawa, Luca Bogoni, 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: 20200104984
    Abstract: Method and system for reducing a number of eigenvectors. For example, a computer-implemented method for reducing a number of eigenvectors, the method comprising: obtaining a plurality of to-be-processed matrices; mapping the plurality of to-be-processed matrices to a space of symmetric positive definite matrices to form a Riemannian manifold corresponding to a Riemannian kernel function; obtaining a kernel-function matrix by using at least a principal component analysis to calculate one or more inner products of the mapped plurality of matrices based on at least the Riemannian kernel function; calculating a first group of eigenvectors of the kernel-function matrix, the first group of eigenvectors including a first number of eigenvectors; and selecting one or more eigenvectors from the first group of eigenvectors to obtain a second group of eigenvectors, the second group of eigenvectors including a second number of eigenvectors; wherein the second number is less than the first number.
    Type: Application
    Filed: August 29, 2019
    Publication date: April 2, 2020
    Inventors: XIAODAN XING, FENG SHI, 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: 20200074712
    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: Application
    Filed: July 3, 2019
    Publication date: March 5, 2020
    Inventors: Dijia Wu, Yaozong Gao, Yiqiang Zhan
  • Patent number: 10580159
    Abstract: A framework for coarse orientation detection in image data. In accordance with one aspect, the framework trains a learning structure to recognize a coarse orientation of the anatomical structure of interest based on training images. The framework may then pass one or more current images through the trained learning structure to generate a coarse orientation of the anatomical structure of interest. The framework then outputs the generated coarse orientation of the anatomical structure of interest.
    Type: Grant
    Filed: January 23, 2018
    Date of Patent: March 3, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Fitsum Aklilu Reda, Parmeet Singh Bhatia, Yiqiang Zhan, Xiang Sean Zhou
  • Patent number: 10460508
    Abstract: A framework for facilitating visualization, including localizing at least one anatomical structure of interest in image data. The structure of interest is then highlighted by reformatting the image data by mapping landmarks associated with the structure of interest to corresponding points along a contour of a geometric shape and warping the image data based on the mapped landmarks. The resulting reformatted image data is rendered for display to a user.
    Type: Grant
    Filed: June 10, 2015
    Date of Patent: October 29, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Yiqiang Zhan, Gerardo Hermosillo-Valadez, Xiang Sean Zhou, Matthias Fenchel, Berthold Kiefer
  • Publication number: 20190307366
    Abstract: In a method for alpha angle measurements of a bone joint based on magnetic resonance imaging (MRI) data of the bone joint, a three-dimensional (3D) bone surface image of the bone joint is generated based on two-dimensional (2D) segmentations on radial plane slices of the bone joint. Based on the 3D bone surface image, a head center of a head of the bone joint and a neck axis of a neck of the bone joint are estimated. An alpha angle model is constructed based on the estimated head center and neck axis. Further, the alpha angle measurement is determined for each of the radial plane slices of the bone joint based on the constructed alpha angle model.
    Type: Application
    Filed: April 9, 2019
    Publication date: October 10, 2019
    Inventors: Liang Zhao, Esther Raithel, Yiqiang Zhan
  • Publication number: 20190311228
    Abstract: A framework for cross-modality image synthesis. A first and second model may be trained using respective first and second pairs of complementary images and corresponding first and second ground truth images that represent first and second views of a region of interest. The first and second pairs of complementary images may be acquired by a first modality and the first and second ground truth images may be acquired by a second modality. A combinational network may further be trained to combine features from the first and second models. At least one synthetic second modality image may then be generated by passing current images through the trained first or second model and the combinational network, wherein the current images are acquired by the first modality and represent the first or second view of the region of interest.
    Type: Application
    Filed: January 28, 2019
    Publication date: October 10, 2019
    Inventors: Yu Zhao, Yimo Gao, Shu Liao, Liang Zhao, Zhennan Yan, Yiqiang Zhan, Xiang Sean Zhou
  • Patent number: 10390886
    Abstract: A framework for pedicle screw positioning is described herein. In accordance with one aspect, the framework segments at least one vertebra of interest in image data. The framework then automatically determines a pedicle region within the segmented vertebra of interest, and a safe region within the segmented vertebra of interest. An optimal insertion path passing through the pedicle region may then be generated within the safe region.
    Type: Grant
    Filed: September 30, 2016
    Date of Patent: August 27, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Mingzhong Li, Shu Liao, Fitsum Aklilu Reda, Yiqiang Zhan, Xiang Sean Zhou, Gerhard Kleinszig