Patents by Inventor Yaozong Gao
Yaozong Gao 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).
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Patent number: 11836925Abstract: A system for image segmentation is provided. The system may obtain a target image including an ROI, and segment a preliminary region representative of the ROI from the target image using a first ROI segmentation model corresponding to a first image resolution. The system may segment a target region representative of the ROI from the preliminary region using a second ROI segmentation model corresponding to a second image resolution. At least one model of the first and second ROI segmentation models may at least include a first convolutional layer and a second convolutional layer downstream to the first convolutional layer. A count of input channels of the first convolutional layer may be greater than a count of output channels of the first convolutional layer, and a count of input channels of the second convolutional layer may be smaller than a count of output channels of the second convolutional layer.Type: GrantFiled: May 22, 2022Date of Patent: December 5, 2023Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Miaofei Han, Yaozong Gao, Yu Zhang, Yiqiang Zhan
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Patent number: 11694086Abstract: The present disclosure provides a region of interest (ROI) detection system. The system may be configured to acquire a target image and an ROI detection model, and perform ROI detection on the target image by applying the ROI detection model to the target image. The ROI detection model may be a trained cascaded neural network including a plurality of sequentially connected trained models. The plurality of trained models may include a trained first model and at least one trained second model downstream to the trained first model in the trained cascaded neural network. The plurality of trained models may be sequentially trained. Each of the trained second model may be trained using a plurality of training samples determined based on one or more trained models of the plurality of trained models generated before the generation of the trained second model.Type: GrantFiled: November 22, 2021Date of Patent: July 4, 2023Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yaozong Gao, Yanbo Chen, Jiyong Wang, Weiyang Xie, Yiqiang Zhan
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Publication number: 20230157659Abstract: A method for lung nodule evaluation is provided. The method may include obtaining a target image including at least a portion of a lung of a subject. The method may also include segmenting, from the target image, at least one target region each of which corresponds to a lung nodule of the subject. The method may further include generating an evaluation result with respect to the at least one lung nodule based on the at least one target region.Type: ApplicationFiled: January 19, 2023Publication date: May 25, 2023Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Wenhai ZHANG, Ying SHAO, Yaozong GAO
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Patent number: 11605164Abstract: A method for lung nodule evaluation is provided. The method may include obtaining a target image including at least a portion of a lung of a subject. The method may also include segmenting, from the target image, at least one target region each of which corresponds to a lung nodule of the subject. The method may further include generating an evaluation result with respect to the at least one lung nodule based on the at least one target region.Type: GrantFiled: October 16, 2020Date of Patent: March 14, 2023Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Wenhai Zhang, Ying Shao, Yaozong Gao
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Publication number: 20220284687Abstract: A system for image segmentation is provided. The system may obtain a target image including an ROI, and segment a preliminary region representative of the ROI from the target image using a first ROI segmentation model corresponding to a first image resolution. The system may segment a target region representative of the ROI from the preliminary region using a second ROI segmentation model corresponding to a second image resolution. At least one model of the first and second ROI segmentation models may at least include a first convolutional layer and a second convolutional layer downstream to the first convolutional layer. A count of input channels of the first convolutional layer may be greater than a count of output channels of the first convolutional layer, and a count of input channels of the second convolutional layer may be smaller than a count of output channels of the second convolutional layer.Type: ApplicationFiled: May 22, 2022Publication date: September 8, 2022Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Miaofei HAN, Yaozong GAO, Yu ZHANG, Yiqiang ZHAN
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Patent number: 11348233Abstract: The present disclosure provides systems and methods for image processing. The method may include obtaining an initial image; obtaining an intermediate image corresponding to the initial image, the intermediate image including pixels or voxels associated with at least a portion of a target object in the initial image; obtaining a trained processing model; and generating, based on the initial image and the intermediate image, a target image associated with the target object using the trained processing model.Type: GrantFiled: December 28, 2019Date of Patent: May 31, 2022Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yaozong Gao, Wenhai Zhang, Yiqiang Zhan
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Patent number: 11341734Abstract: A system for image segmentation is provided. The system may obtain a target image including an ROI, and segment a preliminary region representative of the ROI from the target image using a first ROI segmentation model corresponding to a first image resolution. The system may segment a target region representative of the ROI from the preliminary region using a second ROI segmentation model corresponding to a second image resolution. At least one model of the first and second ROI segmentation models may at least include a first convolutional layer and a second convolutional layer downstream to the first convolutional layer. A count of input channels of the first convolutional layer may be greater than a count of output channels of the first convolutional layer, and a count of input channels of the second convolutional layer may be smaller than a count of output channels of the second convolutional layer.Type: GrantFiled: May 9, 2020Date of Patent: May 24, 2022Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Miaofei Han, Yu Zhang, Yaozong Gao, Yiqiang Zhan
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Patent number: 11290530Abstract: Sharing media items includes receiving, on a first device, user input indicating a request for media items on a second device, wherein the request identifies an object represented in the media items, obtaining, on a requesting device, an object model for the object, generating a pull request comprising pull request parameters, wherein the pull request parameters comprise the object model, and transmitting the pull request from the first device to the second device, wherein the object model identifies the object represented in the media items.Type: GrantFiled: December 17, 2018Date of Patent: March 29, 2022Assignee: Apple Inc.Inventors: Vinay Sharma, Sergiy Buyanov, Yaozong Gao
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Publication number: 20220083804Abstract: The present disclosure provides a region of interest (ROI) detection system. The system may be configured to acquire a target image and an ROI detection model, and perform ROI detection on the target image by applying the ROI detection model to the target image. The ROI detection model may be a trained cascaded neural network including a plurality of sequentially connected trained models. The plurality of trained models may include a trained first model and at least one trained second model downstream to the trained first model in the trained cascaded neural network. The plurality of trained models may be sequentially trained. Each of the trained second model may be trained using a plurality of training samples determined based on one or more trained models of the plurality of trained models generated before the generation of the trained second model.Type: ApplicationFiled: November 22, 2021Publication date: March 17, 2022Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yaozong GAO, Yanbo CHEN, Jiyong WANG, Weiyang XIE, Yiqiang ZHAN
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Patent number: 11270157Abstract: The present disclosure provides a system and method for classification determination of a structure. The method may include obtaining image data representing a structure of a subject. The method may also include determining a plurality of candidate classifications of the structure and their respective probabilities by inputting the image data into a classification model. The classification model may include a backbone network for determining a backbone feature of the structure, a segmentation network for determining a segmentation feature of the structure, and a density classification network for determining a density feature of the structure. The method may further include determining a target classification of the structure based on at least a part of the probabilities of the plurality of candidate classifications.Type: GrantFiled: December 27, 2019Date of Patent: March 8, 2022Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yanbo Chen, Yaozong Gao, Yiqiang Zhan
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Patent number: 11188773Abstract: The present disclosure provides a region of interest (ROI) detection system. The system may be configured to acquire a target image and an ROI detection model, and perform ROI detection on the target image by applying the ROI detection model to the target image. The ROI detection model may be a trained cascaded neural network including a plurality of sequentially connected trained models. The plurality of trained models may include a trained first model and at least one trained second model downstream to the trained first model in the trained cascaded neural network. The plurality of trained models may be sequentially trained. Each of the trained second model may be trained using a plurality of training samples determined based on one or more trained models of the plurality of trained models generated before the generation of the trained second model.Type: GrantFiled: October 14, 2019Date of Patent: November 30, 2021Assignee: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yaozong Gao, Yanbo Chen, Jiyong Wang, Weiyang Xie, Yiqiang Zhan
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Publication number: 20210304896Abstract: A method is provided. The method may also include generating at least one first segmentation image and at least one second segmentation image based on the target image. Each of the at least one first segmentation image may indicate one of the at least one target region of the subject. Each of the at least one second segmentation image may indicate a lesion region of one of the at least one target region. The method may also include determining first feature information relating to the at least one lesion region and the at least one target region based on the at least one first segmentation image and the at least one second segmentation image. The method may further include generating a diagnosis result with respect to the subject based on the first feature information.Type: ApplicationFiled: March 31, 2021Publication date: September 30, 2021Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yanbo CHEN, Yaozong GAO, Yanping YANG
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Publication number: 20210118130Abstract: A method for lung nodule evaluation is provided. The method may include obtaining a target image including at least a portion of a lung of a subject. The method may also include segmenting, from the target image, at least one target region each of which corresponds to a lung nodule of the subject. The method may further include generating an evaluation result with respect to the at least one lung nodule based on the at least one target region.Type: ApplicationFiled: October 16, 2020Publication date: April 22, 2021Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Wenhai ZHANG, Ying SHAO, Yaozong GAO
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Patent number: 10950026Abstract: Method and system for displaying a medical image. For example, a computer-implemented method for displaying a medical image includes acquiring an original image of a target; obtaining a lesion region in the original image; selecting a region of interest in the original image based on at least the lesion region, the region of interest including the lesion region; obtaining a plurality of planar images of the region of interest from the original image of the target based on at least a predetermined setting; generating an animated display by grouping the plurality of planar images based on at least a predetermined order; and displaying the animated display related to the region of interest including the lesion region.Type: GrantFiled: July 3, 2019Date of Patent: March 16, 2021Assignee: Shanghai United Imaging Intelligence Co., Ltd.Inventors: Dijia Wu, Yaozong Gao, Yiqiang Zhan
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Patent number: 10762337Abstract: Training a generative adversarial network (GAN) for use in facial recognition, comprising providing an input image of a particular face into a facial recognition system to obtain a faceprint; obtaining, based on the input faceprint and a noise value, a set of output images from a GAN generator; obtaining feedback from a GAN discriminator, wherein obtaining feedback comprises inputting each output image into the GAN discriminator and determining a set of likelihood values indicative of whether each output image comprises a facial image; determining, based on each output image, a modified noise value; inputting each output image into a second facial recognition network to determine a set of modified faceprints; defining, based on each modified noise value and modified faceprint, feedback for the GAN generator, wherein the feedback comprises a first value and a second value; and modifying control parameters of the GAN generator.Type: GrantFiled: May 30, 2018Date of Patent: September 1, 2020Assignee: Apple Inc.Inventors: Vinay Sharma, Yaozong Gao
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Publication number: 20200272841Abstract: A system for image segmentation is provided. The system may obtain a target image including an ROI, and segment a preliminary region representative of the ROI from the target image using a first ROI segmentation model corresponding to a first image resolution. The system may segment a target region representative of the ROI from the preliminary region using a second ROI segmentation model corresponding to a second image resolution. At least one model of the first and second ROI segmentation models may at least include a first convolutional layer and a second convolutional layer downstream to the first convolutional layer. A count of input channels of the first convolutional layer may be greater than a count of output channels of the first convolutional layer, and a count of input channels of the second convolutional layer may be smaller than a count of output channels of the second convolutional layer.Type: ApplicationFiled: May 9, 2020Publication date: August 27, 2020Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Miaofei HAN, Yu ZHANG, Yaozong GAO, Yiqiang ZHAN
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Publication number: 20200211188Abstract: The present disclosure provides systems and methods for image processing. The method may include obtaining an initial image; obtaining an intermediate image corresponding to the initial image, the intermediate image including pixels or voxels associated with at least a portion of a target object in the initial image; obtaining a trained processing model; and generating, based on the initial image and the intermediate image, a target image associated with the target object using the trained processing model.Type: ApplicationFiled: December 28, 2019Publication date: July 2, 2020Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yaozong GAO, Wenhai ZHANG, Yiqiang ZHAN
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Publication number: 20200210761Abstract: The present disclosure provides a system and method for classification determination of a structure. The method may include obtaining image data representing a structure of a subject. The method may also include determining a plurality of candidate classifications of the structure and their respective probabilities by inputting the image data into a classification model. The classification model may include a backbone network for determining a backbone feature of the structure, a segmentation network for determining a segmentation feature of the structure, and a density classification network for determining a density feature of the structure. The method may further include determining a target classification of the structure based on at least a part of the probabilities of the plurality of candidate classifications.Type: ApplicationFiled: December 27, 2019Publication date: July 2, 2020Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yanbo CHEN, Yaozong GAO, Yiqiang ZHAN
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Publication number: 20200167586Abstract: The present disclosure provides a region of interest (ROI) detection system. The system may be configured to acquire a target image and an ROI detection model, and perform ROI detection on the target image by applying the ROI detection model to the target image. The ROI detection model may be a trained cascaded neural network including a plurality of sequentially connected trained models. The plurality of trained models may include a trained first model and at least one trained second model downstream to the trained first model in the trained cascaded neural network. The plurality of trained models may be sequentially trained. Each of the trained second model may be trained using a plurality of training samples determined based on one or more trained models of the plurality of trained models generated before the generation of the trained second model.Type: ApplicationFiled: October 14, 2019Publication date: May 28, 2020Applicant: SHANGHAI UNITED IMAGING INTELLIGENCE CO., LTD.Inventors: Yaozong GAO, Yanbo CHEN, Jiyong WANG, Weiyang XIE, Yiqiang ZHAN
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Publication number: 20200074712Abstract: Method and system for displaying a medical image. For example, a computer-implemented method for displaying a medical image includes acquiring an original image of a target; obtaining a lesion region in the original image; selecting a region of interest in the original image based on at least the lesion region, the region of interest including the lesion region; obtaining a plurality of planar images of the region of interest from the original image of the target based on at least a predetermined setting; generating an animated display by grouping the plurality of planar images based on at least a predetermined order; and displaying the animated display related to the region of interest including the lesion region.Type: ApplicationFiled: July 3, 2019Publication date: March 5, 2020Inventors: Dijia Wu, Yaozong Gao, Yiqiang Zhan