Patents Examined by Xin Jia
  • Patent number: 11232354
    Abstract: An apparatus and computer-implemented method for training a machine-learning algorithm to perform histopathological analysis is disclosed. The method comprises obtaining (210) a plurality of first microscopic images of first histological specimens that have been stained with a first marker; and obtaining (212), a respective plurality of second microscopic images of second histological specimens that have been stained with a second, different marker. The method further comprises obtaining (220) a respective plurality of mask images generated for the second microscopic images, each mask image identifying a histological feature of interest highlighted in the respective second microscopic image by the second marker. The method comprises training (240) the machine-learning algorithm to predict, from a first microscopic image, a histological feature of interest that would be highlighted in the same specimen by the second marker.
    Type: Grant
    Filed: September 7, 2018
    Date of Patent: January 25, 2022
    Assignee: ROOM4 GROUP LIMITED
    Inventors: John Robert Maddison, Havard Danielsen
  • Patent number: 11232859
    Abstract: The application relates to a computer implemented method for determining a basal and an apex plane in a set of Magnetic Resonance, MR, image slices of a heart, wherein the set of MR image slices comprises short axis views of the heart obtained over the heartbeat. The set of MR image slices is applied to a multitask deep learning artificial intelligence Model which is configured to identify a basal plane slice and an apex plane slice on the applied set of image slices, wherein the multitask deep learning artificial intelligence model is further configured to determine at least one further parameter of cardiac anatomy or of a cardiac function. A first output of the multitask deep learning artificial intelligence Model is determined as the apex plane slice and a second output as the basal plane slice. At least one further output of the multitask deep learning artificial intelligence Model is determined as the at least one further parameter of the cardiac anatomy or of the cardiac function.
    Type: Grant
    Filed: September 4, 2020
    Date of Patent: January 25, 2022
    Assignee: Siemens Healthcare GmbH
    Inventors: Andrei Bogdan Gheorghita, Lucian Mihai Itu, Puneet Sharma, Teodora Chitiboi
  • Patent number: 11234046
    Abstract: A system and method for associating an audio signal with a Personal Mobile Device (PMD) of a user is provided and includes associating a user with the Personal Mobile Device (PMD) of a user, associating at least one of the user and the PMD with a processing device, determining if the user is using an exercise machine having an exercise machine television and identifying which exercise machine the user is using, determining which channel is being displayed on the exercise machine television and transmitting the audio signal for the channel being displayed available to the user's PMD.
    Type: Grant
    Filed: October 17, 2017
    Date of Patent: January 25, 2022
    Assignee: MYE Entertainment Inc.
    Inventors: Anthony E. Garcia, Ronald G. Pace, Sean McKirdy
  • Patent number: 11216674
    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting locations in an environment of a vehicle where objects are likely centered and determining properties of those objects. One of the methods includes receiving an input characterizing an environment external to a vehicle. For each of a plurality of locations in the environment, a respective first object score that represents a likelihood that a center of an object is located at the location is determined. Based on the first object scores, one or more locations from the plurality of locations are selected as locations in the environment at which respective objects are likely centered. Object properties of the objects that are likely centered at the selected locations are also determined.
    Type: Grant
    Filed: April 20, 2020
    Date of Patent: January 4, 2022
    Assignee: Waymo LLC
    Inventors: Abhijit Ogale, Alexander Krizhevsky
  • Patent number: 11210783
    Abstract: A method of processing plaques in magnetic resonance imaging of vessel wall include: step S101, training a generative adversarial network and a capsule neural network to obtain a trained generator network and a trained capsule neural network; and step S102, cascade-connecting the trained generator network with the capsule neural network into a system to recognize and classify plaques in magnetic resonance imaging of vessel wall. In one aspect, the capsule neural network has more abundant vascular plaques characteristic information represented by vector; in another aspect, when the trained generator network and the capsule neural network are cascaded into the system to recognize and classify the plaques in magnetic resonance imaging of vessel wall, an accuracy of recognition and classification may be greatly improved. A device for processing the method as well as a computer for implementing are also disclosed.
    Type: Grant
    Filed: June 24, 2020
    Date of Patent: December 28, 2021
    Assignee: Shenzhen Institutes of Advanced Technology
    Inventors: Hairong Zheng, Xin Liu, Na Zhang, Zhanli Hu, Dong Liang, Yongfeng Yang
  • Patent number: 11206562
    Abstract: An apparatus determining characteristics of radios within a communications network includes a radio, RF signal sensor, analyzer, and computer. The radio transmits RF signals, has transmission operating parameters with respective predetermined values having respective thresholds and a identifier, and has an air operating mode where signals comprise the identifier. The sensor receives the signals having characteristics correlating with the operating parameters. While the signals are received during the operating mode, the analyzer measures the signal characteristics and determines health of the radio by analyzing whether the measured characteristics transmitted are within the respective thresholds of the values, and concludes that health is acceptable if the measured characteristics are within the thresholds, and concludes that health is unacceptable if at least one measured characteristic is outside a threshold.
    Type: Grant
    Filed: March 30, 2020
    Date of Patent: December 21, 2021
    Assignee: Locus Location Systems, LLC
    Inventors: John McCarthy, Joseph Rey
  • Patent number: 11206057
    Abstract: There is provided a capacitive communication system including an object and a capacitive touch panel. The object includes a plurality of induction conductors configured to have different potential distributions at different time intervals by modulating respective potentials thereof. The capacitive touch panel includes a plurality of sensing electrodes configured to form a coupling electric field with the induction conductors to detect the different potential distributions at the different time intervals. When the different potential distributions match a predetermined agreement between the object and the capacitive touch panel, a near field communication is formed between the object and the capacitive touch panel.
    Type: Grant
    Filed: January 8, 2020
    Date of Patent: December 21, 2021
    Assignee: PIXART IMAGING INC.
    Inventors: Yung-Wei Chen, Yen-Chang Wang, Yen-Min Chang, Hsin-Chia Chen
  • Patent number: 11205509
    Abstract: The present invention relates to an image processing device (10) comprising a data input (11) for receiving volumetric image data comprising a plurality of registered volumetric images of an imaged object, a noise modeler (12) for generating a noise model indicative of a spatial distribution of noise in each of the plurality of registered volumetric images, a feature detector (13) for detecting a plurality of image features taking the volumetric image data into account, and a marker generator (14) for generating a plurality of references indicating feature positions of a subset of the plurality of detected image features, in which said subset corresponds to the detected image features that are classified as difficult to discern on a reference volumetric image in the plurality of registered volumetric images based on a classification and/or a visibility criterium, wherein the classification and/or the visibility criterium takes the or each noise model into account.
    Type: Grant
    Filed: October 2, 2018
    Date of Patent: December 21, 2021
    Assignee: KONINKLIJKE PHILIPS N.V.
    Inventor: Liran Goshen
  • Patent number: 11200405
    Abstract: A three-dimensional (3D) image-based facial verification method and apparatus is provided. The facial verification method may include capturing a facial image of a 3D face of a user, determining an occluded region in the captured facial image by comparing the captured facial image and an average facial image, generating a synthetic image by synthesizing the captured facial image and the average facial image based on the occluded region, and verifying the user based on the synthetic image.
    Type: Grant
    Filed: May 30, 2019
    Date of Patent: December 14, 2021
    Assignee: Samsung Electronics Co., Ltd.
    Inventors: Seungju Han, Minsu Ko, Jaejoon Han, Chang Kyu Choi
  • Patent number: 11200978
    Abstract: An information processing apparatus includes an obtaining unit, an inference section, and a selection unit. The obtaining unit is configured to obtain a temporal subtraction image between a first medical image captured at a first point of time and a second medical image captured at a second point of time. The inference section includes a plurality of inference units, each for making an inference from the temporal subtraction image. The selection unit is configured to select, based on a region of interest in the obtained temporal subtraction image, at least one inference unit from the plurality of inference units in the inference section. In response to being selected by the selection unit, the at least one inference unit so selected makes the inference from the temporal subtraction image.
    Type: Grant
    Filed: March 30, 2020
    Date of Patent: December 14, 2021
    Assignee: CANON KABUSHIKI KAISHA
    Inventor: Masami Kawagishi
  • Patent number: 11200463
    Abstract: A method is provided for adapting an image impression of an image, in particular of an image acquired in the context of medical imaging.
    Type: Grant
    Filed: October 9, 2019
    Date of Patent: December 14, 2021
    Assignee: Siemens Healthcare GmbH
    Inventors: Annette Birkhold, Christian Kaethner, Markus Kowarschik
  • Patent number: 11200460
    Abstract: An object of the invention is to provide an image learning device, an image learning method, a neural network, and an image classification device which can support appropriate classification of an image. In the image learning device according to an aspect of the invention, the neural network performs a first task of classifying a recognition target in a medical image and outputting a classification score as an evaluation result, and a second task different from the first task. The neural network updates a weight coefficient on the basis of a comparison result between the classification score output for the medical image of a first image group and a ground truth classification label, and does not reflect the classification score output for the medical image of a second image group in an update of the weight coefficient, for the first task.
    Type: Grant
    Filed: November 4, 2020
    Date of Patent: December 14, 2021
    Assignee: FUJIFILM Corporation
    Inventor: Shumpei Kamon
  • Patent number: 11195262
    Abstract: A method for identifying a body region in a medical image includes obtaining a medical image including a number of consecutive bio-section images, inputting the medical image into a preset machine learning model to obtain a numerical value for each of the bio-section images corresponding to the body region to which the bio-section image belongs, determining whether the numerical values of the medical image are abnormal, adjusting the numerical values when the numerical values are abnormal, determining the body region corresponding to the numerical values or the adjusted numerical values, and labeling the body region in the medical image and outputting the labeled medical image. The bio-section images are cross-sectional images of a living body.
    Type: Grant
    Filed: May 27, 2020
    Date of Patent: December 7, 2021
    Assignee: COHESION INFORMATION TECHNOLOGY CORP.
    Inventors: Feng-Mao Lin, Chi-Wen Chen, Wei-Da Huang, Liangtsan Gary Wu
  • Patent number: 11188774
    Abstract: There are proposed an attention memory method and system for locating an object through visual dialogue. The attention memory system for identifying an object on an image includes: a control unit which generates a question for identifying a preset object on the image, derives an answer to the generated question, and identifies the preset object on the image based on the question and the answer; and memory which stores the image. The control unit generates the question by incorporating information about objects included in the image into the question, and updates the information about the objects based on the answer.
    Type: Grant
    Filed: June 29, 2018
    Date of Patent: November 30, 2021
    Assignee: SEOUL NATIONAL UNIVERSITY R&DB FOUNDATION
    Inventors: Byoung-Tak Zhang, Cheolho Han, Yu-Jung Heo, Wooyoung Kang, Jaehyun Jun
  • Patent number: 11176384
    Abstract: An apparatus for object detection around a vehicle includes an imaging device mounted on the vehicle and a computing device. The imaging device is used to capture a video of an exterior environment of the vehicle. The computing device is used to execute a DSFPN module in order to provide a DSFPN model detector, which functions as a perception unit to process and analyze the video captured by the imaging device and to estimate a scale, a location and categories of an object. The DSFPN model detector includes a bottom-up subnet provided with auxiliary prediction heads, and a top-down subnet provided with prediction heads. When the DSFPN model detector is performed in a model training stage, both the prediction heads and the auxiliary prediction heads are used. In a detection stage, only the prediction heads are used in the DSFPN model detector, and the auxiliary prediction heads are removed.
    Type: Grant
    Filed: September 18, 2020
    Date of Patent: November 16, 2021
    Assignee: XMOTORS.AI INC.
    Inventors: Fan Yang, Tianshuo Zhang, Cheng Lu, Yandong Guo
  • Patent number: 11164048
    Abstract: A method is described for generating a prediction of a disease classification error for a magnified, digital microscope slide image of a tissue sample. The image is composed of a multitude of patches or tiles of pixel image data. An out-of-focus degree per patch is computed using a machine learning out-of-focus classifier. Data representing expected disease classifier error statistics of a machine learning disease classifier for a plurality of out-of-focus degrees is retrieved. A mapping of the expected disease classifier error statistics to each of the patches of the digital microscope slide image based on the computed out-of-focus degree per patch is computed, thereby generating a disease classifier error prediction for each of the patches. The disease classifier error predictions thus generated are aggregated over all of the patches.
    Type: Grant
    Filed: May 26, 2020
    Date of Patent: November 2, 2021
    Assignee: Google LLC
    Inventors: Martin Stumpe, Timo Kohlberger
  • Patent number: 11157744
    Abstract: Automated detection and approximation of objects in a video, including: (a) sampling a provided digital video, to obtain a set of sampled frames; (b) applying an object detection algorithm to the sampled frames, to detect objects appearing in the sampled frames; (c) based on the detections in the sampled frames, applying an object approximation algorithm to each sequence of frames that lie between the sampled frames, to approximately detect objects appearing in each of the sequences; (d) applying a trained regression model to each of the sequences, to estimate a quality of the approximate detection of objects in the respective sequence; (e) applying the object detection algorithm to one or more frames in those of the sequences whose quality of the approximate detection is below a threshold, to detect objects appearing in those frames.
    Type: Grant
    Filed: January 15, 2020
    Date of Patent: October 26, 2021
    Assignee: International Business Machines Corporation
    Inventors: Udi Barzelay, Tal Hakim, Daniel Nechemia Rotman, Dror Porat
  • Patent number: 11157763
    Abstract: A system and method for identifying and subsequently modifying target sections within images is disclosed. The method includes receiving a user request that includes a target image and a user input, such that the user input includes an action corresponding to the target image. The method further includes extracting a plurality of target image attributes from the user input and comparing the plurality of target image attributes with a set of attributes within a pattern attribute table. The pattern attribute table includes mapping of each of the set of attributes to an associated set of activated neurons within a neural network. Comparing the plurality of target image further includes identifying a set of activated neurons mapped to the matching attribute as neuron activations corresponding to the plurality of target image attributes. The method includes identifying a target image section based on the set of activated neurons using a back-propagation technique.
    Type: Grant
    Filed: March 23, 2020
    Date of Patent: October 26, 2021
    Assignee: Wipro Limited
    Inventor: Manjunath Ramachandra Iyer
  • Patent number: 11158094
    Abstract: A nuclear medicine image reconstruction method generates a reconstructed image (44) by performing iterative image in reconstruction (30, 130) on nuclear medicine imaging data (22). The iterative image reconstruction produces a sequence of update images (34, 36, 134, 136). During the iterative image reconstruction, a standardized uptake value (SUV) transform (40) is applied to convert an update image (34, 36) to an update SUV image (42, 46). The SUV transform scales values of voxels of the update image to SUV values using scaling factors including at least a body size metric and a dose metric. During the iterative image reconstruction, at least one parameter used in an image update of the iterative image reconstruction is adjusted using the update SUV image. For example, a parameter of a prior or filter (38) incorporated into an image reconstruction update step (32) or used in filtering of an update image (36) may be adjusted.
    Type: Grant
    Filed: January 3, 2018
    Date of Patent: October 26, 2021
    Assignee: KONINKLIJKE PHILIPS N.V.
    Inventors: Bin Zhang, Chuanyong Bai, Shushen Lin, Andriy Andreyev, Zhiqiang Hu
  • Patent number: 11144766
    Abstract: Fast visual data annotation includes automatic detection using an automatic detector to detect subjects and joints in video frames. Then, annotation with sampling is performed, including determining when a frame is a sample (e.g., based on comparison of frames). Replay and refinement is utilized where user is involved with manually annotating subjects and/or joints in only select video frames.
    Type: Grant
    Filed: September 25, 2019
    Date of Patent: October 12, 2021
    Assignee: Sony Group Corporation
    Inventor: Cheng-Yi Liu