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1.发明授权公开(公告)号：US11921278B2
公开(公告)日：2024-03-05
申请号：US17373416
申请日：2021-07-12
Inventor： Baochang Han , Xiao Han
CPC classification number: G02B21/367 , G02B21/006 , G06F18/22 , G06T7/0002 , G06T7/20 , G06V20/69 , G06T2207/10056
Abstract: A method comprises obtaining a pathology image set using a microscope, the pathology image set including at least a to-be-evaluated image and one or more associated images, the associated images and the to-be-evaluated image are consecutive frame images acquired using the microscope. The method comprises determining a first status corresponding to the to-be-evaluated image according to the pathology image set, the first status being used for indicating a motion change of the to-be-evaluated image during the acquisition and the first status includes a plurality of predefined states. The method comprises in accordance with a determination that the first status corresponds to a static state of the plurality of predefined states, determining a second status corresponding to the to-be-evaluated image, the second status indicating a change in image clarity of the to-be-evaluated image. This application further discloses an image status determining apparatus, a device, and a computer storage medium.
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2.发明申请公开(公告)号：US20210341725A1
公开(公告)日：2021-11-04
申请号：US17373416
申请日：2021-07-12
Inventor： Baochang HAN , Xiao Han
Abstract: A method comprises obtaining a pathology image set using a microscope, the pathology image set including at least a to-be-evaluated image and one or more associated images, the associated images and the to-be-evaluated image are consecutive frame images acquired using the microscope. The method comprises determining a first status corresponding to the to-be-evaluated image according to the pathology image set, the first status being used for indicating a motion change of the to-be-evaluated image during the acquisition and the first status includes a plurality of predefined states. The method comprises in accordance with a determination that the first status corresponds to a static state of the plurality of predefined states, determining a second status corresponding to the to-be-evaluated image, the second status indicating a change in image clarity of the to-be-evaluated image. This application further discloses an image status determining apparatus, a device, and a computer storage medium.
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公开(公告)号：US12235425B2
公开(公告)日：2025-02-25
申请号：US17405833
申请日：2021-08-18
Inventor： Jun Liao , Jianhua Yao , Xiao Han
Abstract: This disclosure discloses a microscope system, a smart medical device, an automatic focusing method, and a storage medium. The smart medical device includes an objective lens, a beam splitter, an image projector assembly, a camera assembly, and a focusing device. The objective lens includes a first end and a second end, and the first end faces a to-be-observed sample. The beam splitter is disposed on the second end. The image projector assembly is in communication with the beam splitter, the image projector assembly includes a first lens and an image projection device, and light generated by the image projector assembly enters the beam splitter through the first lens. The camera assembly includes a camera. The focusing device is disposed on the camera assembly, and the focusing device is configured to perform focus adjustment on the camera.
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公开(公告)号：US12047683B2
公开(公告)日：2024-07-23
申请号：US17510290
申请日：2021-10-25
Inventor： Jingwen Ye , Baochang Han , Xiao Han
CPC classification number: H04N23/73 , G02B21/365 , G06T1/0007 , G06T7/0012 , G16H30/40 , H04N1/40012 , H04N23/71 , G06T2207/30004
Abstract: This application relates to an image acquisition method and apparatus, a device, and a storage medium, and relates to the field of image processing technologies. The method includes obtaining a first image, the first image being an image acquired by controlling an exposure time of an image acquisition component according to a brightness reference value; obtaining an exposure state of the first image; updating the brightness reference value according to the exposure state of the first image, to obtain an updated brightness reference value; controlling the exposure time of the image acquisition component according to the updated brightness reference value; and acquiring a second image.
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5.发明授权公开(公告)号：US12223645B2
公开(公告)日：2025-02-11
申请号：US17701910
申请日：2022-03-23
Inventor： De Cai , Hu Ye , Zhaoxuan Ma , Xiao Han
Abstract: Methods, apparatus, device, and storage medium for identifying an abnormal cell in a to-be-detected sample are disclosed. The method includes obtaining, by a device, multi-layer images of a to-be-detected sample, the to-be-detected sample comprising a single cell and a cell cluster; obtaining, by the device, multi-layer image blocks of the single cell and multi-layer image blocks of the cell cluster according to the multi-layer images; obtaining, by the device, a first identification result by a first image identification network according to the multi-layer image blocks of the single cell; obtaining, by the device, a second identification result by a second image identification network according to the multi-layer image blocks of the cell cluster; and determining, by the device, whether an abnormal cell exists in the to-be-detected sample according to the first identification result and the second identification result.
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Patent Agency Ranking
公开(公告)号：US12260623B2
公开(公告)日：2025-03-25
申请号：US17707045
申请日：2022-03-29
Inventor： Jun Zhang , Kuan Tian , Kezhou Yan , Jianhua Yao , Xiao Han
IPC: G06K9/00 , G06T7/11 , G06T7/194 , G06V10/774 , G06V10/82
Abstract: Embodiments of this application disclose a method and apparatus for training an image region segmentation model, and an image region segmentation method and apparatus. The method includes acquiring a sample image set, and each image of the sample image set having first annotation information; generating graph structure data corresponding to a sample image in the sample image set, the graph structure data comprising multiple nodes, and each node comprising at least one pixel in the sample image; determining second annotation information of each node according to the graph structure data and the first annotation information corresponding to the sample image by using a graph convolutional network model, a granularity of the second annotation information being smaller than a granularity of the first annotation information, the graph convolutional network model being a part of an image segmentation model; and training the image segmentation model according to the second annotation information.
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公开(公告)号：US12046056B2
公开(公告)日：2024-07-23
申请号：US17379839
申请日：2021-07-19
Inventor： Hu Ye , Xiao Han , Kaiwen Xiao , Niyun Zhou , Mingyang Chen
CPC classification number: G06V20/698 , G06T3/147 , G06T7/0012 , G06V10/945 , G16H30/40
Abstract: A computer device obtains a to-be-annotated image having a first magnification. The device obtains an annotated image from an annotated image set, the annotated image distinct from the to-be-annotated image and having a second magnification that is distinct from with the first magnification. The annotated image set includes at least one annotated image. The device matches the to-be-annotated image with the annotated image to obtain an affine transformation matrix, and generates annotation information of the to-be-annotated image according to the affine transformation matrix and the annotated image. In this way, annotations corresponding to images at different magnifications may be migrated. For example, the annotations may be migrated from the low-magnification images to the high-magnification images, thereby reducing the manual annotation amount and avoiding repeated annotations, and further improving annotation efficiency and reducing labor costs.
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公开(公告)号：US11967069B2
公开(公告)日：2024-04-23
申请号：US17515170
申请日：2021-10-29
Inventor： Jun Zhang , Kezhou Yan , Jianhua Yao , Xiao Han
IPC: G06T7/00 , G06T7/11 , G06T7/136 , G06T7/187 , G06T7/70 , G06V20/69 , G16H10/40 , G16H30/40 , G16H50/20 , G16H70/60
CPC classification number: G06T7/0012 , G06T7/11 , G06T7/136 , G06T7/187 , G06T7/70 , G06V20/695 , G06V20/698 , G16H10/40 , G16H30/40 , G16H50/20 , G16H70/60 , G06T2207/10056 , G06T2207/20036 , G06T2207/30024 , G06T2207/30096 , G06T2207/30242 , G06V2201/03
Abstract: This application provides a pathological section image processing method performed by a computer device. The method includes: obtaining stained images of a pathological section after cell membrane staining; determining cell nucleus positions of cancer cells in a stained image under an ith field of view in the n fields of view; generating a cell membrane description result of the stained image under the ith field of view, the cell membrane description result being used for indicating completeness and staining intensity of the cell membrane staining; determining quantities of cells of types in the stained image under the ith field of view according to the cell nucleus positions and the cell membrane description result; and determining an analysis result of the pathological section according to quantities of the cells of types in the stained images under the n fields of view.
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公开(公告)号：US11908188B2
公开(公告)日：2024-02-20
申请号：US17225966
申请日：2021-04-08
Inventor： Weijia Lu , Jianhua Yao , Xiao Han , Niyun Zhou
CPC classification number: G06V20/41 , G02B21/365 , G06N3/045 , G06T7/0012 , G06V20/46 , G06T2207/10056
Abstract: Embodiments of this application disclose methods, systems, and devices for medical image analysis and medical video stream processing. In one aspect, a method comprises extracting video frames from a medical image video stream that includes at least two pathological-section-based video frames. The method also comprises identifying single-frame image features in the video frames, mapping the single-frame image features into single-frame diagnostic classification results, and performing a classification mapping based on a video stream feature sequence that comprises the single-frame image features. The classification mapping comprises performing a convolution operation on the video stream feature sequence through a preset convolutional layer, obtaining a convolution result in accordance with the convolution operation, and performing fully connected mapping on the convolution result through a preset fully connected layer. In accordance with the classification mapping, a target diagnostic classification result corresponding to the medical image video stream is determined.
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10.发明授权公开(公告)号：US11790672B2
公开(公告)日：2023-10-17
申请号：US17482177
申请日：2021-09-22
Inventor： Baochang Han , Xiao Han , Yong Chen , Peng Yang
CPC classification number: G06V20/695 , G02B21/34 , G02B21/367 , G06T7/62 , G06T2207/10056
Abstract: Embodiments of the present disclosure provide an image processing method based on artificial intelligence (AI) and an image processing system. The method includes: obtaining a feature recognition result of an image by performing image processing on the image to recognize a feature of the image and the image being obtained by performing image acquisition on a section of a patient using a digital slide scanner to generate a whole slide image (WSI) as the image; determining an imaging area of the section within a field of view of an eyepiece of a microscope with which real-time imaging is performed on the section; determining, within the image, an image area corresponding to the imaging area of the section and acquiring, from the feature recognition result of the image, a target feature recognition result of the image area; and superimposing the target feature recognition result on the imaging area of the section.
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