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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
发明人： Baochang Han , Xiao Han
CPC分类号： G02B21/367 , G02B21/006 , G06F18/22 , G06T7/0002 , G06T7/20 , G06V20/69 , G06T2207/10056
摘要： 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
发明人： Baochang HAN , Xiao Han
摘要： 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：US12047683B2
公开(公告)日：2024-07-23
申请号：US17510290
申请日：2021-10-25
发明人： Jingwen Ye , Baochang Han , Xiao Han
CPC分类号： H04N23/73 , G02B21/365 , G06T1/0007 , G06T7/0012 , G16H30/40 , H04N1/40012 , H04N23/71 , G06T2207/30004
摘要： 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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公开(公告)号：US12046056B2
公开(公告)日：2024-07-23
申请号：US17379839
申请日：2021-07-19
发明人： Hu Ye , Xiao Han , Kaiwen Xiao , Niyun Zhou , Mingyang Chen
IPC分类号： G16H30/40 , G06F16/51 , G06T3/147 , G06T7/00 , G06V10/94 , G06V20/69 , G16H30/20 , G16H50/70
CPC分类号： G06V20/698 , G06T3/147 , G06T7/0012 , G06V10/945 , G16H30/40
摘要： 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
发明人： Jun Zhang , Kezhou Yan , Jianhua Yao , Xiao Han
IPC分类号： G06T7/00 , G06T7/11 , G06T7/136 , G06T7/187 , G06T7/70 , G06V20/69 , G16H10/40 , G16H30/40 , G16H50/20 , G16H70/60
CPC分类号： 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
摘要： 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
发明人： Weijia Lu , Jianhua Yao , Xiao Han , Niyun Zhou
CPC分类号： G06V20/41 , G02B21/365 , G06N3/045 , G06T7/0012 , G06V20/46 , G06T2207/10056
摘要： 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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公开(公告)号：US11790672B2
公开(公告)日：2023-10-17
申请号：US17482177
申请日：2021-09-22
发明人： Baochang Han , Xiao Han , Yong Chen , Peng Yang
CPC分类号： G06V20/695 , G02B21/34 , G02B21/367 , G06T7/62 , G06T2207/10056
摘要： 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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8.发明公开公开(公告)号：US20230237771A1
公开(公告)日：2023-07-27
申请号：US18127657
申请日：2023-03-29
CPC分类号： G06V10/7715 , G06T7/0012 , G06T2207/20081 , G06V2201/031
摘要： The present application provides a self-supervised learning method performed by a computer device. The method includes: performing a data enhancement on an original medical image to obtain a first enhanced image and a second enhanced image, the first enhanced image and the second enhanced image being positive samples of each other; performing feature extractions on the first enhanced image and the second enhanced image by a feature extraction model to obtain a first image feature of the first enhanced image and a second image feature of the second enhanced image; determining a model loss of the feature extraction model based on the first image feature, the second image feature, and a negative sample image feature, the negative sample image feature being an image feature corresponding to other original medical images; and training the feature extraction model based on the model loss.
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公开(公告)号：US20210224546A1
公开(公告)日：2021-07-22
申请号：US17225966
申请日：2021-04-08
发明人： Weijia Lu , Jianhua Yao , Xiao Han , Niyun Zhou
摘要： 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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公开(公告)号：US20240273720A1
公开(公告)日：2024-08-15
申请号：US18641184
申请日：2024-04-19
发明人： Zhongyi Yang , Sen Yang , Jinxi Xiang , Jun Zhang , Xiao Han
CPC分类号： G06T7/0012 , G06T3/40 , G06T7/11 , G06T7/194 , G06V10/42 , G06V10/44 , G06V10/764 , G06T2207/20076 , G06T2207/20081 , G06T2207/30096 , G06V2201/03
摘要： This application discloses a method for determining a lesion region, and a model training method and apparatus, and relates to the field of computer vision technologies. The method includes the following steps: sampling a pathological image by a first sampling way to obtain at least two first instance images (310); determining a candidate lesion region in the pathological image, based on feature information extracted from the at least two first instance images (320); sampling the candidate lesion region by a second sampling way to obtain at least two second instance images, where an overlap degree between the second instance images is greater than that between the first instance images (330); and determining lesion indication information of the pathological image, based on feature information extracted from the at least two second instance images, where the lesion indication information is used for indicating the lesion region in the pathological image (340). In this application, the consumption of human resources is reduced, and costs required to determine the lesion region are saved.
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