Patents by Inventor Jianming Liang

Jianming Liang 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: 20210150710
    Abstract: Not only is annotating medical images tedious and time consuming, but it also demands costly, specialty-oriented expertise, which is not easily accessible. To address this challenge, a new self-supervised framework is introduced: TransVW (transferable visual words), exploiting the prowess of transfer learning with convolutional neural networks and the unsupervised nature of visual word extraction with bags of visual words, resulting in an annotation-efficient solution to medical image analysis. TransVW was evaluated using NIH ChestX-ray14 to demonstrate its annotation efficiency. When compared with training from scratch and ImageNet-based transfer learning, TransVW reduces the annotation efforts by 75% and 12%, respectively, in addition to significantly accelerating the convergence speed. More importantly, TransVW sets new records: achieving the best average AUC on all 14 diseases, the best individual AUC scores on 10 diseases, and the second best individual AUC scores on 3 diseases.
    Type: Application
    Filed: November 15, 2020
    Publication date: May 20, 2021
    Inventors: Mohammad Reza Hosseinzadeh Taher, Fatemeh Haghighi, Jianming Liang
  • Patent number: 11009270
    Abstract: A heat pump air conditioning system and a control method. The heat pump air conditioning system includes: a compressor; an indoor unit heat exchanger, an outdoor unit heat exchanger and a throttling device; a refrigerant circulation loop, connecting the compressor, the indoor unit heat exchanger, the outdoor unit heat exchanger and the throttling device in series; the heat storage module, disposed in the refrigerant circulation loop and configured to absorb heat from refrigerant in the refrigerant circulation loop and store heat when heat storage is required, and to heat the refrigerant in the refrigerant circulation loop when the outdoor unit heat exchanger defrosting is required. The heat pump air conditioning system can store excess heat of the system for defrosting when indoor heat load is low, and release heat for defrosting by means of the heat storage module during a defrosting process while continuing supplying heat to a room.
    Type: Grant
    Filed: January 31, 2018
    Date of Patent: May 18, 2021
    Assignee: GREE ELECTRIC APPLIANCES, INC. OF ZHUHAI
    Inventors: Mingzhu Dong, Jianming Tan, Guanghui Xia, Bo Liang, Xianlin Wang, Xiaocheng Lai, Junhong Wu, Guangqian Peng, Xu Gao, Zhiwei Chen, Bo Yu, Wen Che, Xiaoyu Li
  • Publication number: 20210091975
    Abstract: A method for control of a soft generic routing encapsulation (GRE) tunnel based on client activity includes: receiving a data packet from a first external; storing an identifier associated with the first external device in a client table and a corresponding timestamp associated with receipt of the data packet; creating a soft GRE tunnel between a local interface of the computing device and a remote gateway; updating the client table, wherein updating the client table includes adding a new identifier and corresponding timestamp associated with additional external devices upon receipt of respective data packets, and updating the time stamp corresponding to the respective identifier upon receipt of an additional packet from an additional external device; and halting a GRE health-check process associated with the soft GRE tunnel once a predetermined period of time has elapsed since the timestamp corresponding to each identifier stored in the client table.
    Type: Application
    Filed: December 21, 2017
    Publication date: March 25, 2021
    Inventors: Jianxiang CHEN, Jianming LIANG
  • Patent number: 10956785
    Abstract: Methods, systems, and media for selecting candidates for annotation for use in training classifiers are provided. In some embodiments, the method comprises: identifying, for a trained Convolutional Neural Network (CNN), a group of candidate training samples, wherein each candidate training sample includes a plurality of patches; for each patch of the plurality of patches, determining a plurality of probabilities, each probability being a probability that the patch corresponds to a label of a plurality of labels; identifying a subset of the patches in the plurality of patches; for each patch in the subset of the patches, calculating a metric that indicates a variance of the probabilities assigned to each patch; selecting a subset of the candidate training samples based on the metric; labeling candidate training samples in the subset of the candidate training samples by querying an external source; and re-training the CNN using the labeled candidate training samples.
    Type: Grant
    Filed: April 29, 2019
    Date of Patent: March 23, 2021
    Assignee: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY
    Inventors: Jianming Liang, Zongwei Zhou, Jae Shin
  • Patent number: 10861151
    Abstract: Mechanisms for simultaneously monitoring colonoscopic video quality and detecting polyps in colonoscopy are provided. In some embodiments, the mechanisms can include a quality monitoring system that uses a first trained classifier to monitor image frames from a colonoscopic video to determine which image frames are informative frames and which image frames are non-informative frames. The informative image frames can be passed to an automatic polyp detection system that uses a second trained classifier to localize and identify whether a polyp or any other suitable object is present in one or more of the informative image frames.
    Type: Grant
    Filed: August 8, 2016
    Date of Patent: December 8, 2020
    Assignee: THE ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY
    Inventors: Jianming Liang, Nima Tajbakhsh
  • Publication number: 20200380695
    Abstract: Methods, systems, and media for segmenting images are provided. In some embodiments, the method comprises: generating an aggregate U-Net comprised of a plurality of U-Nets, wherein each U-Net in the plurality of U-Nets has a different depth, wherein each U-Net is comprised of a plurality of nodes Xi,j, wherein i indicates a down-sampling layer the U-Net, and wherein j indicates a convolution layer of the U-Net; training the aggregate U-Net by: for each training sample in a group of training samples, calculating, for each node in the plurality of nodes Xi,j, a feature map xi,j, wherein xi,j is based on a convolution operation performed on a down-sampling of an output from Xi?1,j when j=0, and wherein xi,j is based on a convolution operation performed on an up-sampling operation of an output from Xi+1,j?1 when j>0; and predicting a segmentation of a test image using the trained aggregate U-Net.
    Type: Application
    Filed: May 28, 2020
    Publication date: December 3, 2020
    Inventors: Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, Jianming Liang
  • Publication number: 20200364477
    Abstract: Methods, systems, and media for discriminating and generating translated images are provided. In some embodiments, the method comprises: identifying a set of training images, wherein each image is associated with at least one domain from a plurality of domains; training a generator network to generate: i) a first fake image that is associated with a first domain; and ii) a second fake image that is associated with a second domain; training a discriminator network, using as inputs to the discriminator network: i) an image from the set of training images; ii) the first fake image; and iii) the second fake image; and using the generator network to generate, for an image not included in the set of training images at least one of: i) a third fake image that is associated with the first domain; and ii) a fourth fake image that is associated with the second domain.
    Type: Application
    Filed: May 15, 2020
    Publication date: November 19, 2020
    Inventors: Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Ruibin Feng, Nima Tajbakhsh, Jianming Liang
  • Publication number: 20200251939
    Abstract: A ceiling fan has a motor and multiple fan blades. The motor has a stator assembly and a rotor assembly. The stator frame has a frame, a stator core, and multiple coils. The frame has multiple branch containers and multiple protrusions on the branch containers. The stator core is securely mounted in the frame. The coils are wound on the branch containers and protrusions. Therefore, the coils may be an ellipse and thus the magnetic flux therein is larger, which converts electric energy torques to drive the rotor assembly in higher efficiency. Besides, the rotor has multiple magnetic components and each magnetic component has a magnetic pole. An amount of the magnetic poles is larger than that of the branch containers. The motor can provide a higher torque even at a lower rotating speed.
    Type: Application
    Filed: November 11, 2019
    Publication date: August 6, 2020
    Inventors: JIANSHENG ZHANG, RUHUI HUANG, HANHUA HUANG, JIANMING LIANG
  • Patent number: 10610203
    Abstract: Methods, systems, and media for determining carotid intima-media thickness are provided. In some embodiments, a method for determining carotid intima-media thickness of a carotid artery is provided, the method comprising: receiving a frame from a plurality of images, wherein each of the plurality of images includes a portion of the carotid artery; receiving a user selection of a location with the frame; setting a region of interest, based on the received user selection; detecting a first border and a second border within the region of interest; applying one or more active contour models to the first border and the second border to generate a smoothed first border and a smoothed second border; and calculating the intima-media thickness based at least in part on the smoothed first border and the second smoothed border.
    Type: Grant
    Filed: February 13, 2012
    Date of Patent: April 7, 2020
    Assignees: The Arizona Board of Regents on Behalf of Arizona State University, The Mayo Foundation for Medical Education and Research
    Inventors: Jianming Liang, Xiangjun Zhu, Christopher B. Kendall, Robert T. Hurst
  • Publication number: 20200074701
    Abstract: Detecting a pulmonary embolism (PE) in an image dataset of a blood vessel involves obtaining a volume of interest (VOI) in the blood vessel, generating a plurality of PE candidates within the VOI, generating a set of voxels for each PE candidate, estimating for each PE candidate an orientation of the blood vessel that contains the PE candidate, given the set of voxels for the PE candidate, and generating a visualization of the blood vessel that contains the PE candidate using the estimated orientation of the blood vessel that contains the PE candidate.
    Type: Application
    Filed: August 29, 2019
    Publication date: March 5, 2020
    Inventors: Jianming Liang, Nima Tajbakhsh, Jaeyul Shin
  • Publication number: 20200074271
    Abstract: Disclosed are provided systems, methods, and apparatuses for implementing a multi-resolution neural network for use with imaging intensive applications including medical imaging. For example, a system having means to execute a neural network model formed from a plurality of layer blocks including an encoder layer block which precedes a plurality of decoder layer blocks includes: means for associating a resolution value with each of the plurality of layer blocks; means for processing via the encoder layer block a respective layer block input including a down-sampled layer block output processing, via decoder layer blocks, a respective layer block input including an up-sampled layer block output and a layer block output of a previous layer block associated with a prior resolution value of a layer block which precedes the respective decoder layer block; and generating the respective layer block output by summing or concatenating the processed layer block inputs.
    Type: Application
    Filed: August 29, 2019
    Publication date: March 5, 2020
    Inventors: Jianming Liang, Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh
  • Publication number: 20190332896
    Abstract: Methods, systems, and media for selecting candidates for annotation for use in training classifiers are provided. In some embodiments, the method comprises: identifying, for a trained Convolutional Neural Network (CNN), a group of candidate training samples, wherein each candidate training sample includes a plurality of patches; for each patch of the plurality of patches, determining a plurality of probabilities, each probability being a probability that the patch corresponds to a label of a plurality of labels; identifying a subset of the patches in the plurality of patches; for each patch in the subset of the patches, calculating a metric that indicates a variance of the probabilities assigned to each patch; selecting a subset of the candidate training samples based on the metric; labeling candidate training samples in the subset of the candidate training samples by querying an external source; and re-training the CNN using the labeled candidate training samples.
    Type: Application
    Filed: April 29, 2019
    Publication date: October 31, 2019
    Inventors: Jianming Liang, Zongwei Zhou, Jae Shin
  • Patent number: 10328282
    Abstract: A system and methods are provided for generating intensity modulated proton therapy plans robust to various kinds of delivery uncertainties with the capability for treatment planners to control the balance between plan quality and robustness. The system obtains a representation of a subject and a proton beam configuration that describes a number of beamlets and their respective arrangement. The system computes an objective function, in the treatment planning system, first part of which is about dose deviations from the prescribed dose in the target volumes, second part of which is about dose deviations from the dose constraint in the non-target volumes, and computing dose volume constraints for targets using a probability to control the dose distribution in the target volumes to be between a lower threshold and an upper threshold. Based on this information, the system obtains a robust chance-constrained treatment planning model with a user-adjustable tolerance level.
    Type: Grant
    Filed: July 13, 2016
    Date of Patent: June 25, 2019
    Assignees: Mayo Foundation for Medical Education and Research, Arizona Board of Regents on behalf of Arizona State University
    Inventors: Yu An, Jianming Liang, Wei Liu
  • Patent number: 10157467
    Abstract: A system and method for detecting central pulmonary embolisms in a subject's vasculature is provided. In some aspects, the method includes receiving, using the input, a set of images representing a vasculature of the subject's lungs, automatically analyzing the set of images to segment the main arteries associated with the subject's lungs and separate the main arteries from surrounding tissues. The method also includes automatically extracting central pulmonary embolism candidates from the set of images after segmenting and separating the main arteries, and automatically evaluating the central pulmonary embolism candidates in three-dimensional (3D) space by applying a series of rules. The method further includes automatically displaying a report indicating evaluated central pulmonary embolism candidates on a display.
    Type: Grant
    Filed: August 8, 2016
    Date of Patent: December 18, 2018
    Assignees: Arizona Board of Regents on Behalf of Arizona State University, Mayo Foundation For Medical Education And Research
    Inventors: Esra Dincer, Michael Gotway, Jianming Liang
  • Patent number: 10120980
    Abstract: Improved pulmonary embolism (PE) detection may be obtained through computer aided-diagnosis. In particular, PE detection may be accomplished through patient-level diagnosis, embolus-level detection, or a combination of the two. Patient-level diagnosis operates to quickly exclude non-PE patients and dispatch PE-patients to treatment. Embolus-level detection operates to localize individual emboli to support personalized medicine via risk stratification. Multiple instance-based learning (MIBL) classification at the patient level explores the key observation that once any TP candidate of a patient is classified as positive, the patient is identified as PE positive. That is, MIBL focuses on correct classification of patients rather than individual candidates, to effectively and rapidly distinguish between PE patients and non-PE patients.
    Type: Grant
    Filed: January 27, 2015
    Date of Patent: November 6, 2018
    Assignee: Arizona Board of Regents on Behalf of Arizona State University
    Inventor: Jianming Liang
  • Publication number: 20180314943
    Abstract: Systems for selecting candidates for labelling and use in training a convolutional neural network (CNN) are provided, the systems comprising: a memory device; and at least one hardware processor configured to: receive a plurality of input candidates, wherein each candidate includes a plurality of identically labelled patches; and for each of the plurality of candidates: determine a plurality of probabilities, each of the plurality of probabilities being a probability that a unique patch of the plurality of identically labelled patches of the candidate corresponds to a label using a pre-trained CNN; identify a subset of candidates of the plurality of input candidates, wherein the subset does not include all of the plurality of candidates, based on the determined probabilities; query an external source to label the subset of candidates to produce labelled candidates; and train the pre-trained CNN using the labelled candidates.
    Type: Application
    Filed: April 27, 2018
    Publication date: November 1, 2018
    Inventors: Jianming Liang, Zongwei Zhou, Jae Shin
  • Patent number: 10055843
    Abstract: A system and methods for detecting polyps using optical images acquired during a colonoscopy. In some aspects, a method includes receiving the set of optical images from the input and generating polyp candidates by analyzing the received set of optical images. The method also includes generating a plurality of image patches around locations associated with each polyp candidate, applying a set of convolutional neural networks to the corresponding image patches, and computing probabilities indicative of a maximum response for each convolutional neural network. The method further includes identifying polyps using the computed probabilities for each polyp candidate, and generating a report indicating identified polyps.
    Type: Grant
    Filed: March 31, 2016
    Date of Patent: August 21, 2018
    Assignees: Mayo Foundation for Medical Education and Research, Arizona Board of Regents on behalf of Arizona State University
    Inventors: Nima Tajbakhsh, Suryakanth R. Gurudu, Jianming Liang
  • Patent number: 10052027
    Abstract: A system and methods for polyp detection using optical colonoscopy images are provided. In some aspects, the system includes an input configured to receive a series of optical images, and a processor configured to process the series of optical images with steps comprising of receiving an optical image from the input, constructing an edge map corresponding to the optical image, the edge map comprising a plurality of edge pixel, and generating a refined edge map by applying a classification scheme based on patterns of intensity variation to the plurality of edge pixels in the edge map. The processor may also process the series with steps of identifying polyp candidates using the refined edge map, computing probabilities that identified polyp candidates are polyps, and generating a report, using the computed probabilities, indicating detected polyps. The system also includes an output for displaying the report.
    Type: Grant
    Filed: June 8, 2017
    Date of Patent: August 21, 2018
    Assignees: Mayo Foundation for Medical Education and Research, Arizona Board of Regents on behalf of Arizona State University
    Inventors: Nima Tajbakhsh, Jianming Liang, Suryakanth R. Gurudu
  • Publication number: 20180225820
    Abstract: Mechanisms for simultaneously monitoring colonoscopic video quality and detecting polyps in colonoscopy are provided. In some embodiments, the mechanisms can include a quality monitoring system that uses a first trained classifier to monitor image frames from a colonoscopic video to determine which image frames are informative frames and which image frames are non-informative frames. The informative image frames can be passed to an automatic polyp detection system that uses a second trained classifier to localize and identify whether a polyp or any other suitable object is present in one or more of the informative image frames.
    Type: Application
    Filed: August 8, 2016
    Publication date: August 9, 2018
    Applicant: Arizona Board of Regents on behalf of Arizona State University
    Inventors: Jianming Liang, Nima Tajbakhsh
  • Patent number: 9978142
    Abstract: A system for quality assessment of optical colonoscopy images includes an input device configured to acquire a series of images during an optical colonoscopy. A computing device is coupled in communication with the input device and configured to acquire from the input device an input image from the series of images captured during the optical colonoscopy; form a cell grid including a plurality of cells on the input image; perform an image transformation onto the input image with each cell of the plurality of cells within the cell grid; reconstruct each cell to form a reconstructed image; compute a difference image of a sum of a plurality of differences between the input image and the reconstructed image; compute a histogram of the difference image; and apply a probabilistic classifier to the histogram to calculate an informativeness score for the input image.
    Type: Grant
    Filed: April 24, 2015
    Date of Patent: May 22, 2018
    Assignees: Arizona Board of Regents on Behalf of Arizona State University, Mayo Foundation for Medical Education and Research
    Inventors: Changching Chi, Nima Tajbakhsh, Haripriya Sharma, Suryakanth Gurudu, Jianming Liang