Patents by Inventor Xiang Sean Zhou

Xiang Sean Zhou 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).

  • Publication number: 20200380475
    Abstract: A method is for inserting a further data block into a first ledger, the first ledger including data blocks. In an embodiment, the method includes receiving a further medical dataset via an interface; determining the further data block via a calculation unit. The further data block includes the further medical dataset and a further link information. The further link information includes a hash of at least one of the data blocks of the first ledger. Finally, in an embodiment the method includes inserting the further data block into the first ledger via the calculation unit.
    Type: Application
    Filed: February 25, 2019
    Publication date: December 3, 2020
    Applicant: Siemens Healthcare GmbH
    Inventors: Benedikt KRUEGER, Thomas FRIESE, Thomas GOSSLER, Tilo CHRIST, Michael KELM, Moritz UEBLER, Friedrich HEGENDOERFER, Frank STEINMETZ, Markus KIRCHNER, Tobias HARTMANN, Michael ROMMEL, Swen CAMPAGNA, Xiang Sean ZHOU, Eric ALBRECHT, Robert SOELLNER
  • 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: 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: 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: 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: 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
  • 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
  • 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: 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
  • Patent number: 10304198
    Abstract: A framework for automatic retrieval of medical images. In accordance with one aspect, the framework detects patches in a query image volume that contain at least a portion of an anatomical region of interest by using a first trained classifier. The framework determines disease probabilities by applying a second trained classifier to the detected patches, and selects, from the patches, a sub-set of informative patches with disease probabilities above a pre-determined threshold value. For a given patch from the sub-set of informative patches, the framework retrieves, from a database, patches that are most similar to the given image. Image volumes associated with the retrieved patches are then retrieved from the database. A report based on the retrieved image volumes may then be generated and presented.
    Type: Grant
    Filed: September 15, 2017
    Date of Patent: May 28, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Zhennan Yan, Yiqiang Zhan, Shu Liao, Yoshihisa Shinagawa, Xiang Sean Zhou, Matthias Wolf
  • Publication number: 20190019287
    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: Application
    Filed: June 25, 2018
    Publication date: January 17, 2019
    Inventors: Fitsum Aklilu Reda, Yiqiang Zhan, Parmeet Singh Bhatia, Yoshihisa Shinagawa, Luca Bogoni, Xiang Sean Zhou
  • Publication number: 20180218516
    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: Application
    Filed: January 23, 2018
    Publication date: August 2, 2018
    Inventors: Fitsum Aklilu Reda, Parmeet Singh Bhatia, Yiqiang Zhan, Xiang Sean Zhou
  • Patent number: 9972093
    Abstract: A method for automatically detecting a region of interest in a digital medical image, comprising over-segmenting the image into a plurality of superpixels through use of an over-segmentation algorithm; for each pair of neighboring superpixels in the plurality of superpixels, computing, through a machine learning algorithm, the probability of each pair being in one of three predetermined classes; for each superpixel in the plurality of superpixels, computing a probability of the superpixel being in the region of interest; generating an edge map from computing each pixel's value based on the computed superpixel probabilities; applying an extended Hough transform to the generated edge map to generate a Hough parameter counting space; determining the optimal quadrilateral in the Hough parameter counting space by excluding false positive edges; and designating the region of interest as being within the boundary of the determined optimal quadrilateral.
    Type: Grant
    Filed: March 14, 2016
    Date of Patent: May 15, 2018
    Assignee: Siemens Healthcare GmbH
    Inventors: Liang Zhao, Zhigang Peng, Xiang Sean Zhou
  • Publication number: 20180089840
    Abstract: A framework for automatic retrieval of medical images. In accordance with one aspect, the framework detects patches in a query image volume that contain at least a portion of an anatomical region of interest by using a first trained classifier. The framework determines disease probabilities by applying a second trained classifier to the detected patches, and selects, from the patches, a sub-set of informative patches with disease probabilities above a pre-determined threshold value. For a given patch from the sub-set of informative patches, the framework retrieves, from a database, patches that are most similar to the given image. Image volumes associated with the retrieved patches are then retrieved from the database. A report based on the retrieved image volumes may then be generated and presented.
    Type: Application
    Filed: September 15, 2017
    Publication date: March 29, 2018
    Inventors: Zhennan Yan, Yiqiang Zhan, Shu Liao, Yoshihisa Shinagawa, Xiang Sean Zhou, Matthias Wolf
  • Patent number: 9741131
    Abstract: Disclosed herein is a framework for facilitating image processing. In accordance with one aspect, the framework receives first image data acquired by a first modality and one or more articulated models. The one or more articulated models may include at least one section image acquired by the first modality and aligned with a local image acquired by a second modality. The framework may align an anatomical region of the first image data with the section image and non-rigidly register a first region of interest extracted from the section image with a second region of interest extracted from the aligned anatomical region. To generate a segmentation mask of the anatomical region, the registered first region of interest may be inversely mapped to a subject space of the first image data.
    Type: Grant
    Filed: July 15, 2014
    Date of Patent: August 22, 2017
    Assignees: Siemens Medical Solutions USA, Inc., Siemens Aktiengesellschaft
    Inventors: Gerardo Hermosillo Valadez, Yiqiang Zhan, Xiang Sean Zhou, Matthias Fenchel, Berthold Kiefer
  • Patent number: 9704300
    Abstract: A framework for anatomy orientation detection is described herein. In accordance with one aspect, a pre-trained regressor is applied to appearance features of the image volume to predict a colatitude of the structure of interest. An optimal longitude corresponding to the predicted colatitude is then determined. In response to the colatitude being more than a pre-determined threshold, the image volume is re-oriented based on the predicted colatitude and the optimal longitude, and the predicted colatitude and optimal longitude determination is repeated for the re-oriented image volume.
    Type: Grant
    Filed: February 18, 2016
    Date of Patent: July 11, 2017
    Assignee: Siemens Medical Solutions USA, Inc.
    Inventors: Fitsum Aklilu Reda, Yiqiang Zhan, Xiang Sean Zhou
  • Publication number: 20170112575
    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: Application
    Filed: September 30, 2016
    Publication date: April 27, 2017
    Inventors: Mingzhong Li, Shu Liao, Fitsum Aklilu Reda, Yiqiang Zhan, Xiang Sean Zhou, Gerhard Kleinszig