Patents by Inventor Yefeng Zheng

Yefeng Zheng 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: 20220233160
    Abstract: This application relates to an image data inspection method and apparatus in the field of artificial intelligence (AI) technologies. The method includes obtaining an image to be inspected, the image to be inspected comprising a sequence of slice images; determining a corresponding group of slice images for each target image in the sequence of slice images; extracting a corresponding slice feature map for each slice image in the group of slice images; aligning the slice feature maps extracted corresponding to the group of slice images; aggregating context information of each slice image in the group of slice images by using an aligned feature map; and performing target region inspection on an aggregated feature map, to obtain an inspection result corresponding to the target image, and combining the inspection result corresponding to each target image, to generate an inspection result corresponding to the image to be inspected.
    Type: Application
    Filed: April 15, 2022
    Publication date: July 28, 2022
    Inventors: Shilei CAO, Hualuo LIU, Yefeng ZHENG
  • Patent number: 11393229
    Abstract: Methods and systems for artificial intelligence based medical image segmentation are disclosed. In a method for autonomous artificial intelligence based medical image segmentation, a medical image of a patient is received. A current segmentation context is automatically determined based on the medical image and at least one segmentation algorithm is automatically selected from a plurality of segmentation algorithms based on the current segmentation context. A target anatomical structure is segmented in the medical image using the selected at least one segmentation algorithm.
    Type: Grant
    Filed: November 24, 2020
    Date of Patent: July 19, 2022
    Assignee: Siemens Healthcare GmbH
    Inventors: Shaohua Kevin Zhou, Mingqing Chen, Hui Ding, Bogdan Georgescu, Mehmet Akif Gulsun, Tae Soo Kim, Atilla Peter Kiraly, Xiaoguang Lu, Jin-hyeong Park, Puneet Sharma, Shanhui Sun, Daguang Xu, Zhoubing Xu, Yefeng Zheng
  • Publication number: 20220222796
    Abstract: An image processing method includes obtaining a sample image and a generative adversarial network (GAN), including a generation network and an adversarial network, and performing style conversion on the sample image, to obtain a reference image. The method further includes performing global style recognition on the reference image, to determine a global style loss between the reference image and the sample image, and performing image content recognition on the reference image and the sample image, to determine a content loss between the reference image and the sample image. The method also includes performing local style recognition on the reference image and the sample image, to determine a local style loss of the reference image and a local style loss of the sample image, training the generation network to obtain a trained generation network, and performing style conversion on a to-be-processed image by using the trained generation network.
    Type: Application
    Filed: March 29, 2022
    Publication date: July 14, 2022
    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: XINPENG XIE, JIAWEI CHEN, YUEXIANG LI, KAI MA, YEFENG ZHENG
  • Publication number: 20220215558
    Abstract: A method for three-dimensional edge detection includes obtaining, for each of plural two-dimensional slices of a three-dimensional image, a two-dimensional object detection result and a two-dimensional edge detection result, stacking the two-dimensional object detection results into a three-dimensional object detection result, and stacking the two-dimensional edge detection results into a three-dimensional edge detection result. The method also includes performing encoding according to a feature map of the three-dimensional image, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an encoding result, and performing decoding according to the encoding result, the three-dimensional object detection result, and the three-dimensional edge detection result, to obtain an optimized three-dimensional edge detection result of the three-dimensional image.
    Type: Application
    Filed: March 24, 2022
    Publication date: July 7, 2022
    Applicant: Tencent Technology (Shenzhen) Company Limited
    Inventors: Luyan LIU, Kai MA, Yefeng ZHENG
  • Publication number: 20220148191
    Abstract: An image segmentation method includes obtaining target domain images and source domain images, and segmenting the source domain images and the target domain images by using a generative network in a first generative adversarial network. The method further includes segmenting the source domain images and the target domain images by using a generative network in a second generative adversarial network, and determining a first source domain image and a second source domain image according to source domain segmentation losses, and determining a first target domain image and a second target domain image according to target domain segmentation losses. The method also includes performing cross training on the first generative adversarial network and the second generative adversarial network to obtain a trained first generative adversarial network; and segmenting a to-be-segmented image based on the generative network in the trained first generative adversarial network.
    Type: Application
    Filed: January 28, 2022
    Publication date: May 12, 2022
    Applicant: Tencent Technology (Shenzhen) Company Limited
    Inventors: Luyan LIU, Kai MA, Yefeng ZHENG
  • Publication number: 20220147151
    Abstract: This application provides a gesture information processing method and apparatus, an electronic device, and a storage medium. The method includes: determining an electromyography signal collection target object in a gesture information usage environment; dividing the electromyography signal sample through a sliding window having a fixed window value and a fixed stride into different electromyography signals of the target object, and denoising the different electromyography signals of the target object; recognizing the denoised different electromyography signals, and determining probabilities of gesture information represented by the different electromyography signals; and weighting the probabilities of the gesture information represented by the different electromyography signals, so as to determine gesture information matching the target object.
    Type: Application
    Filed: January 20, 2022
    Publication date: May 12, 2022
    Inventors: Xiaolin HONG, Qingqing ZHENG, Xinmin WANG, Kai MA, Yefeng ZHENG
  • Publication number: 20220054071
    Abstract: This disclosure discloses a method and apparatus for processing a motor MI-EEG signal and a storage medium. The method includes: inputting a source MI-EEG signal belonging to a source domain and a target MI-EEG signal belonging to a target domain to an initial feature extraction model to obtain first source MI features and first target MI features; inputting the first source MI features to an initial classification model to obtain a first classification result outputted by the initial classification model, the first classification result representing an action predicted to be performed in the source MI-EEG signal; and adjusting a model parameter of the initial feature extraction model and/or a model parameter of the initial classification model when a certain condition (set) is met.
    Type: Application
    Filed: November 1, 2021
    Publication date: February 24, 2022
    Applicant: Tencent Technology (Shenzhen) Company Limited
    Inventors: Mengying LEI, Zijun DENG, He ZHAO, Qingqing ZHENG, Kai MA, Yefeng ZHENG
  • Publication number: 20220051416
    Abstract: The disclosure relates to methods, devices, systems, and computer storage medium for performing medical image segmentation. The method includes: The method includes: obtaining, by a device, a first medical image and a second medical image with a labeled region; performing, by the device, feature extraction on the first medical image and the second medical image respectively, to obtain first feature information of the first medical image and second feature information of the second medical image; obtaining, by the device, optical flow motion information from the second medical image to the first medical image according to the first feature information and the second feature information; and segmenting, by the device, the first medical image according to the optical flow motion information and the labeled region, to obtain a segmentation result of the first medical image.
    Type: Application
    Filed: October 29, 2021
    Publication date: February 17, 2022
    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: Shilei CAO, Yifan HU, Kai MA, Yefeng ZHENG
  • Publication number: 20220036135
    Abstract: A method for determining a target image to be labeled includes: obtaining an original image and an autoencoder (AE) set, the original image being an image having not been labeled, the AE set including N AEs; obtaining an encoded image set corresponding to the original image by using the AE set, the encoded image set including N encoded images, the encoded images being corresponding to the AEs; obtaining the encoded image set and a segmentation result set corresponding to the original image by using an image segmentation network, the image segmentation network including M image segmentation sub-networks, and the segmentation result set including [(N+1)*M] segmentation results; determining labeling uncertainty corresponding to the original image according to the segmentation result set; and determining whether the original image is a target image according to the labeling uncertainty.
    Type: Application
    Filed: October 14, 2021
    Publication date: February 3, 2022
    Inventors: Yifan HU, Yuexiang LI, Yefeng ZHENG
  • Publication number: 20220036550
    Abstract: The present disclosure provides an artificial intelligence-based (AI-based) medical image processing method performed by a computing device, and a non-transitory computer-readable storage medium. The AI-based medical image processing method includes: processing a medical image to generate an encoded intermediate image; processing the encoded intermediate image, to segment a first feature and generate a segmented intermediate image; processing the encoded intermediate image and the segmented intermediate image based on an attention mechanism, to generate a detected intermediate input image; and performing second feature detection on the detected intermediate input image, to determine whether an image region of the detected intermediate input image in which the first feature is located comprises a second feature.
    Type: Application
    Filed: October 15, 2021
    Publication date: February 3, 2022
    Inventors: Fubo ZHANG, Dong WEI, Kai MA, Yefeng ZHENG
  • Publication number: 20220036187
    Abstract: A sample generation method outputs a dummy sample set generated by a trained sample generation network that operates on spliced vectors formed by combining real category feature vectors extracted from real samples with real category label vectors corresponding to the real samples. The trained sample generation network is trained using real samples and dummy samples that are generated by an intermediate sample generation network operating on the spliced vectors. The training includes inputting the real samples and the dummy samples to an intermediate sample discrimination network, performing iterative adversarial training of the intermediate sample generation network and the intermediate sample discrimination network until an iteration stop condition is met. As a result, the dummy sample set output by the trained sample generation network includes dummy samples that are not easily differentiated from real samples and that are already labeled with category information, for accurate use in training classifiers.
    Type: Application
    Filed: October 15, 2021
    Publication date: February 3, 2022
    Applicant: Tencent Technology (Shenzhen) Company Limited
    Inventors: Dong WEI, Kai MA, Yefeng ZHENG
  • Publication number: 20220028087
    Abstract: The present disclosure provides methods, devices, apparatus, and storage medium for determining a target image region of a target object in a target image. The method includes: obtaining a target image comprising a target object; obtaining an original mask and an image segmentation model, the image segmentation model comprising a first unit model and a second unit model; downsampling the original mask based on a pooling layer in the first unit model to obtain a downsampled mask; extracting region convolution feature information of the target image based on a convolution pooling layer in the second unit model and the downsampled mask; updating the original mask according to the region convolution feature information; and in response to the updated original mask satisfying an error convergence condition, determining a target image region of the target object in the target image according to the updated original mask.
    Type: Application
    Filed: October 13, 2021
    Publication date: January 27, 2022
    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: Yifan HU, Yefeng ZHENG
  • Publication number: 20210374475
    Abstract: An image recognition method includes: obtaining a target three-dimensional (3D) image; inputting the target 3D image to a first recognition model; and obtaining the image type of the target 3D image outputted by the first recognition model. The first recognition model is configured to perform image recognition on the target 3D image to obtain an image type of the target 3D image. A convolutional block of the first recognition model is the same as a convolutional block of a second recognition model, and configured to perform image recognition on the target 3D image. The second recognition model is obtained by training an original recognition model using a target training sample, the target training sample including cubes obtained by rotating and sorting N target cubes obtained from a 3D sample image, N being a natural number greater than 1.
    Type: Application
    Filed: August 13, 2021
    Publication date: December 2, 2021
    Inventors: Xinrui Zhuang, Yuexiang Li, Yefeng Zheng
  • Patent number: 11185231
    Abstract: Intelligent multi-scale image parsing determines the optimal size of each observation by an artificial agent at a given point in time while searching for the anatomical landmark. The artificial agent begins searching image data with a coarse field-of-view and iteratively decreases the field-of-view to locate the anatomical landmark. After searching at a coarse field-of view, the artificial agent increases resolution to a finer field-of-view to analyze context and appearance factors to converge on the anatomical landmark. The artificial agent determines applicable context and appearance factors at each effective scale.
    Type: Grant
    Filed: March 25, 2020
    Date of Patent: November 30, 2021
    Assignee: Siemens Healthcare GmbH
    Inventors: Bogdan Georgescu, Florin Cristian Ghesu, Yefeng Zheng, Dominik Neumann, Tommaso Mansi, Dorin Comaniciu, Wen Liu, Shaohua Kevin Zhou
  • Publication number: 20210365741
    Abstract: A computer device obtains a plurality of medical images. The device generates a texture image based on image data of a region of interest in the medical images. The device extracts a local feature from the texture image using a first network model. The device extracts a global feature from the medical images using a second network model. The device fuses the extracted local feature and the extracted global feature to form a fused feature. The device performs image classification based on the fused feature.
    Type: Application
    Filed: August 9, 2021
    Publication date: November 25, 2021
    Inventors: Yifan HU, Yefeng ZHENG
  • Publication number: 20210365717
    Abstract: Embodiments of this disclosure include a method and an apparatus for segmenting a medical image. The method may include obtaining a slice pair comprising two slices and performing feature extraction on each slice in the slice pair, to obtain high-level feature information and low-level feature information of the each slice in the slice pair. The method may further include segmenting a target object in the each slice according to the low-level feature information and the high-level feature information of the slice, to obtain an initial segmentation result of the each slice and fusing the low-level feature information and the high-level feature information of the slices to obtain a fused feature information. The method may further include determining correlation information between the slices according to the fused feature information and generating a segmentation result of the slice pair based on the correlation information and the initial segmentation results of the slices.
    Type: Application
    Filed: July 29, 2021
    Publication date: November 25, 2021
    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: Shilei CAO, Renzhen WANG, Kai MA, Yefeng ZHENG
  • Publication number: 20210251590
    Abstract: This disclosure discloses a CT image generation method and apparatus, a computer device, and a computer-readable storage medium. The method includes: obtaining a first X-ray image and a second X-ray image, the first X-ray image and the second X-ray image being X-ray images acquired for a target object from two orthogonal viewing angles; calling a generator to perform three-dimensional reconstruction on the first X-ray image and the second X-ray image, to obtain a three-dimensional model of the target object; and obtaining a CT image of the target object according to the three-dimensional model of the target object.
    Type: Application
    Filed: April 30, 2021
    Publication date: August 19, 2021
    Applicant: Tencent Technology (Shenzhen) Company Limited
    Inventors: Heng GUO, Xingde YING, Kai MA, Yefeng ZHENG
  • Publication number: 20210248751
    Abstract: Embodiments of this application disclose a brain image segmentation method and apparatus, a network device, and a storage medium. The method includes obtaining, by a device, a to-be-segmented image group comprising a plurality of modal images of a brain. The device includes a memory storing instructions and a processor in communication with the memory. The method further includes performing, by the device, skull stripping according to the plurality of modal images to obtain a skull-stripped mask; separately performing, by the device, feature extraction on the plurality of modal images to obtain extracted features, and fusing the extracted features to obtain a fused feature; segmenting, by the device, encephalic tissues according to the fused feature to obtain an initial segmentation result; and fusing, by the device, the skull-stripped mask and the initial segmentation result to obtain a segmentation result corresponding to the to-be-segmented image group.
    Type: Application
    Filed: April 27, 2021
    Publication date: August 12, 2021
    Applicant: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: Heng GUO, Yuexiang LI, Yefeng ZHENG
  • Publication number: 20210241027
    Abstract: An image segmentation method is provided for a computing device. The method includes obtaining a general tumor image, performing tumor localization on the tumor image to obtain a candidate image indicating a position of a tumor region in the general tumor image, inputting the candidate image to a cascaded segmentation network constructed based on a machine learning model, and performing image segmentation on the general tumor region in the candidate image using a first-level segmentation network and a second-level segmentation network in the cascaded segmentation network to obtain a segmented image.
    Type: Application
    Filed: March 17, 2021
    Publication date: August 5, 2021
    Inventors: Yifan HU, Yefeng ZHENG
  • Publication number: 20210233247
    Abstract: This application relates to a medical image segmentation method, a computer device, and a storage medium. The method includes: obtaining medical image data; obtaining a target object and weakly supervised annotation information of the target object in the medical image data; determining a pseudo segmentation mask for the target object in the medical image data according to the weakly supervised annotation information; and performing mapping on the medical image data by using a preset mapping model based on the pseudo segmentation mask, to obtain a target segmentation result for the target object. Because the medical image data is segmented based on the weakly supervised annotation information, there is no need to annotate information by using much labor during training of the preset mapping model, thereby saving labor costs. The preset mapping model is a model used for mapping the medical image data based on the pseudo segmentation mask.
    Type: Application
    Filed: April 13, 2021
    Publication date: July 29, 2021
    Inventors: Shilei CAO, Kai MA, Yefeng ZHENG