Patents Examined by Jon Chang
  • Patent number: 11360529
    Abstract: A CPU needs to perform reset operation when a secondary arithmetic processing unit controlled by the CPU controls a signal processing circuit. CPU A controls module A. CPU B controls module B. Module A and module B control a signal processing circuit. CPU A and CPU B issue a reset request to the signal processing circuit. The signal processing circuit performs a reset process based on the reset request accepted from the CPU and a control origin identification signal that identifies a CPU as an origin of controlling the module having started a signal processing section.
    Type: Grant
    Filed: April 7, 2020
    Date of Patent: June 14, 2022
    Assignee: RENESAS ELECTRONICS CORPORATION
    Inventors: Hiroshi Ueda, Ryoji Hashimoto, Taku Maekawa, Katsushige Matsubara, Keisuke Matsumoto
  • Patent number: 11357396
    Abstract: Introduced here are diagnostic platforms able to optimize computer-aided diagnostic (CADx) models by simulating the optical performance of an imaging device based on its mechanical components. For example, a diagnostic platform may acquire a source image associated with a confirmed diagnosis of a medical condition, simulate optical performance based on design data corresponding to a virtual prototype of the imaging device, generate a training image by altering the source image based on the optical performance, apply a diagnostic model to the training image, and then determine whether the performance of the diagnostic model meets a specified performance threshold. If the diagnostic model fails to meet the specified performance threshold, the diagnostic platform can automatically optimize the diagnostic model for the imaging device by altering its underlying algorithm(s).
    Type: Grant
    Filed: January 24, 2020
    Date of Patent: June 14, 2022
    Assignee: Verily Life Sciences LLC
    Inventors: Peter Wubbels, Lin Yang, Eliezer Glik, Sam Kavusi
  • Patent number: 11354800
    Abstract: A method for adaptive treatment planning is provided. The method may include obtaining a planning image volume of a subject, a treatment image volume of the subject, and a first treatment plan related to the planning image volume of the subject, each of the planning image volume and the treatment image volume including an ROI of the subject. The method may also include registering the planning image volume and the treatment image volume, and determining a first contour of the ROI in the registered planning image volume and a second contour of the ROI in the registered treatment image volume. The method may also include evaluating whether an error exists in at least one of the registration or the contour determination based on the first contour and the second contour, and determining a second treatment plan with respect to the treatment image volume based on the evaluation result.
    Type: Grant
    Filed: December 27, 2019
    Date of Patent: June 7, 2022
    Assignee: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.
    Inventors: Supratik Bose, Jonathan Maltz, Johannes Stahl
  • Patent number: 11354834
    Abstract: A non-transitory computer-readable medium stores instructions readable and executable by at least one electronic processor (20) to perform an image reconstruction method (100). The method includes: performing iterative image reconstruction of imaging data acquired using an image acquisition device (12); selecting an update image from a plurality of update images produced by the iterative image reconstruction; processing the selected update image to generate a hot spot artifact map; and suppressing hot spots identified by the generated hot spot artifact map in a reconstructed image output by the iterative image reconstruction.
    Type: Grant
    Filed: December 24, 2018
    Date of Patent: June 7, 2022
    Assignee: KONINKLIJKE PHILIPS N.V.
    Inventors: Shekhar Dwivedi, Chuanyong Bai, Andriy Andreyev, Bin Zhang, Zhiqiang Hu
  • Patent number: 11348231
    Abstract: A method for indicating how a cancer patient will respond to a predetermined therapy relies on spatial statistical analysis of classes of cell centers in a digital image of tissue of the cancer patient. The cell centers are detected in the image of stained tissue of the cancer patient. For each cell center, an image patch that includes the cell center is extracted from the image. A feature vector is generated based on each image patch using a convolutional neural network. A class is assigned to each cell center based on the feature vector associated with each cell center. A score is computed for the image of tissue by performing spatial statistical analysis based on classes of the cell centers. The score indicates how the cancer patient will respond to the predetermined therapy. The predetermined therapy is recommended to the patient if the score is larger than a predetermined threshold.
    Type: Grant
    Filed: December 6, 2019
    Date of Patent: May 31, 2022
    Assignee: AstraZeneca Computational Pathology GmbH
    Inventors: Guenter Schmidt, Nicolas Brieu, Ansh Kapil, Jan Martin Lesniak
  • Patent number: 11328418
    Abstract: Disclosed is a method for vein recognition, the method includes: performing a difference operation and a channel connection on two to-be-verified target vein images respectively to obtain a difference image and a two-channel image of the two target vein images; performing the channel connection on the obtained difference image and two-channel image to obtain a three-channel image, so as to use the three-channel image as an input of a CNN network; fine-tuning a pre-trained model SqueezeNet that completes training on an ImageNet; integrating the difference image and the three-channel image through a cascade optimization framework to obtain a recognition result; regarding a pair of to-be-verified images as a sample, transforming the sample, taking the transformed sample as the input of the CNN network, obtaining a recognition result by supervised training on the network.
    Type: Grant
    Filed: March 26, 2020
    Date of Patent: May 10, 2022
    Assignee: Wuyi University
    Inventors: Junying Zeng, Fan Wang, Chuanbo Qin, Boyuan Zhu, Jingming Zhu, Yikui Zhai, Junying Gan
  • Patent number: 11321589
    Abstract: There is provided a medical image segmentation deep-learning model generation apparatus including a training data generation/allocation unit configured to generate a training dataset through a segmentation result value acquired by inputting a given medical image to an original medical image segmentation deep-learning model and a learning control unit configured to acquire temporary weights using output data corresponding to primary learning by inputting good task data and bad task data sampled from primary learning training datasets to the medical image segmentation deep-learning model and configured to update weights by adding gradients acquired using weights acquired using output data corresponding to secondary learning by inputting good task data and bad task data sampled from secondary learning training datasets to the medical image segmentation deep-learning model, wherein the primary learning and the secondary learning are repeated.
    Type: Grant
    Filed: December 6, 2019
    Date of Patent: May 3, 2022
    Assignees: Seoul National University R&DB Foundation, hodooAI Lab Inc.
    Inventors: Jungwoo Lee, Sungyeob Han, Yeongmo Kim, Seokhyeon Ha
  • Patent number: 11315281
    Abstract: The present disclosure relates to a pupil positioning method. The pupil positioning method may include: obtaining an eye image under illumination of a light source; determining a first internal point in a pupil of the eye image; calculating gradient changes of pixel points along a straight line starting from the first internal point toward outside of the pupil; determining a plurality of edge points at an edge of the pupil based on the gradient changes of the pixel points along the straight line; and performing ellipse fitting on the edge points to obtain a pupil center.
    Type: Grant
    Filed: November 19, 2019
    Date of Patent: April 26, 2022
    Assignees: BEIJING BOE OPTOELECTRONICS TECHNOLOGY CO., LTD., BOE TECHNOLOGY GROUP CO., LTD.
    Inventors: Jiankang Sun, Hao Zhang, Lili Chen, Hongzhen Xue, Fuqiang Ma, Minglei Chu, Xi Li
  • Patent number: 11315254
    Abstract: A method and device for stratified image segmentation are provided. The method includes: obtaining a three-dimensional (3D) image data set representative of a region comprising at least three levels of objects; generating a first segmentation result indicating boundaries of anchor-level objects in the region based on a first neural network (NN) model corresponding to the anchor-level objects; generating a second segmentation result indicating boundaries of mid-level objects in the region based on the first segmentation result and a second NN model corresponding to the mid-level objects; and generating a third segmentation result indicating small-level objects in the region based on the first segmentation result, a third NN model corresponding to the small-level objects, and cropped regions corresponding to the small-level objects.
    Type: Grant
    Filed: July 14, 2020
    Date of Patent: April 26, 2022
    Assignee: Ping An Technology (Shenzhen) Co., Ltd.
    Inventors: Dazhou Guo, Dakai Jin, Zhuotun Zhu, Adam P Harrison, Le Lu
  • Patent number: 11308623
    Abstract: Methods, systems, apparatus, and computer programs, for processing images through multiple neural networks that are trained to detect a pancreatic ductal adenocarcinoma. In one aspect, a method includes actions of obtaining a first image that depicts a first volume of voxels, performing coarse segmentation of the first image using a first neural network trained (i) to process images having the first volume of voxels and (ii) to produce first output data, determining a region of interest of the first image based on the coarse segmentation, performing multi-stage fine segmentation on a plurality of other images that are each based on the region of interest of the first image to generate output data for each stage of the multi-stage fine segmentation, and determining based on the first output data and the output data of each stage of the multi-stage fine segmentation, whether the first image depicts a tumor.
    Type: Grant
    Filed: July 9, 2020
    Date of Patent: April 19, 2022
    Assignee: The Johns Hopkins University
    Inventors: Alan Yuille, Elliott Fishman, Zhuotun Zhu, Yingda Xia, Lingxi Xie
  • Patent number: 11308613
    Abstract: Systems and methods for generating a synthesized contrast enhanced medical image are provided. An input medical image is received. A synthesized contrast enhanced medical image is generated based on the input medical image using a trained machine learning based generator network. The synthesized contrast enhanced medical image includes one or more synthesized contrast enhanced regions of pathological tissue. The synthesized contrast enhanced medical image is output.
    Type: Grant
    Filed: June 9, 2020
    Date of Patent: April 19, 2022
    Assignee: Siemens Healthcare GmbH
    Inventors: Teodora Chitiboi, Puneet Sharma
  • Patent number: 11302013
    Abstract: One or more features of a friction ridge signature of a subject may be identified based on information representing a three-dimensional topography of friction ridges of the subject. Information representing the three-dimensional topography of the friction ridges of the subject may be received. One or more level-three features of the friction ridge signature of the subject may be identified based on the information representing the three-dimensional topography of the friction ridges of the subject. The one or more level-three features may include one or more topographical ridge peaks, topographical ridge notches, topographical ridge passes, pores, and/or other information.
    Type: Grant
    Filed: August 10, 2020
    Date of Patent: April 12, 2022
    Assignee: Identification International, Inc.
    Inventors: Richard K. Fenrich, Bryan D. Dickerson
  • Patent number: 11295452
    Abstract: Black borders are detected in an image frame using a grey scale image of the image frame, and an edge image of the image frame. Candidate black borders are identified using maximum grey scale values associated with rows and columns of pixels of the grey scale image of the image frame, and then validated using a sum of grey scale values associated with rows and columns of pixels in the edge image of the image frame. If the validation fails, it is presumed that no black border exists.
    Type: Grant
    Filed: September 16, 2021
    Date of Patent: April 5, 2022
    Assignee: ALPHONSO INC
    Inventor: Pulak Kuli
  • Patent number: 11295864
    Abstract: An apparatus for vascular modeling is disclosed. The apparatus receives medical images from an imaging device that include representations of a coronary vessel tree of a subject recorded at a different viewing angles. The apparatus determines, from a first of the medical images, a first centerline set and first vessel diameters for sample points along the first centerline set, and determines, from a second of the medical images, a second centerline set and second vessel diameters for sample points along the second centerline set. The apparatus determines a correspondence between the first centerline set and the second centerline set, and determines diameters for a combined centerline set based on the correspondence of sample points along the first and second centerline sets. The apparatus provides the combined centerline set for estimating blood flow resistance values of the coronary vessel tree of the subject to determine at least one potential stenosis.
    Type: Grant
    Filed: November 11, 2019
    Date of Patent: April 5, 2022
    Assignee: Cath Works Ltd.
    Inventors: Nessi Benishti, Ifat Lavi, Ran Kornowski, Idit Avrahami, Guy Lavi
  • Patent number: 11276165
    Abstract: A method and a system for training a deep learning model to obtain histopathological information from images.
    Type: Grant
    Filed: June 12, 2018
    Date of Patent: March 15, 2022
    Assignee: Visiopharm A/S
    Inventors: Jeppe Thagaard, Johan Dore Hansen, Thomas Ebstrup, Michael Friis Lippert, Michael Grunkin
  • Patent number: 11276167
    Abstract: An image data processing method is for registering two four-dimensional image data sets, each representative of a time-series of three-dimensional image frames. The method comprises an initial pre-registration step in which 3D image frames of the two image data sets are rotated and translated (16) relative to one another so as to bring into alignment respective dominant motion vectors identified (14) for each, the dominant motion vector being a 3D motion vector representative of motion of an identified three-dimensional sub-region exhibiting maximal spatial displacement over course of the time series.
    Type: Grant
    Filed: November 20, 2018
    Date of Patent: March 15, 2022
    Assignee: KONINKLIJKE PHILIPS N.V.
    Inventors: Hong Liu, Gerardus Henricus Maria Gijsbers, Jean-Luc Francois-Marie Robert
  • Patent number: 11270434
    Abstract: A framework for motion correction in medical image data. In accordance with one aspect, one or more anatomical ranges where motion is expected are identified in a localizer image of a subject. Image reconstruction with motion correction may be performed based on medical image data within the one or more anatomical ranges to generate motion corrected image data. The motion corrected image data may then be combined with non-motion corrected image data to generate final image data.
    Type: Grant
    Filed: August 12, 2020
    Date of Patent: March 8, 2022
    Assignee: Siemens Medical Solutions USA, Inc.
    Inventors: Paul Schleyer, Sebastian Fuerst, Matthew Mitchell
  • Patent number: 11263472
    Abstract: The disclosure includes a system and method for providing visual analysis focalized on a salient event. A video processing application receives a data stream from a capture device, determines an area of interest over an imaging area of the capture device, detects a salient event from the data stream, determines whether a location of the detected salient event is within the area of interest, and in response to the location of the salient event being within the area of interest, identifies a portion of the data stream, based on the salient event, on which to perform an action.
    Type: Grant
    Filed: February 7, 2020
    Date of Patent: March 1, 2022
    Assignee: Ricoh Co., Ltd.
    Inventors: Manuel Martinello, Hector H. Gonzalez-Banos
  • Patent number: 11253213
    Abstract: Methods and systems for detecting a dissection in surface of an elongated structure in a three dimensional medical image. One system includes an electronic processor configured to receive the three dimensional medical image and determine a periphery of the elongated structure included in the three dimensional medical image. The electronic processor is also configured to generate a non-contrast image representing the periphery of the elongated structure and superimpose a contrast image associated with the three dimensional image on top of the non-contrast image to generate a superimposed image. The electronic processor is also configured to detect at least one dissection in the elongated structure using the superimposed image and output a medical report identifying the at least one dissection detected in the elongated structure.
    Type: Grant
    Filed: July 10, 2019
    Date of Patent: February 22, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Mark D. Bronkalla, Ben Graf, Arkadiusz Sitek, Yiting Xie
  • Patent number: 11238626
    Abstract: A method is proposed for generating a series of sections of a microscopic sample (10), in which the sections are detached from the sample (10) by means of a blade (21), collected, and placed onto a transfer device. A sequence in which the sections are detached from the sample is detected; detachment of the sections from the sample (10) and/or collection of the sections and/or placement of the sections onto the transfer device is monitored by means of one or several observation cameras, accompanied by the acquisition of moving-image data; the sections are tracked in the moving-image data; and positions of the sections on the transfer device are correlated, on the basis of the tracking in the moving-image data, with the sequence in which they were detached from the sample.
    Type: Grant
    Filed: December 9, 2019
    Date of Patent: February 1, 2022
    Assignee: LEICA MIKROSYSTEME GMBH
    Inventor: Peer Oliver Kellermann