Invention Grant
- Patent Title: Method and system for digital staining of label-free fluorescence images using deep learning
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Application No.: US17041447Application Date: 2019-03-29
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Publication No.: US11893739B2Publication Date: 2024-02-06
- Inventor: Aydogan Ozcan , Yair Rivenson , Hongda Wang , Zhensong Wei
- Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
- Applicant Address: US CA Oakland
- Assignee: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
- Current Assignee: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
- Current Assignee Address: US CA Oakland
- Agency: VISTA IP LAW GROUP LLP
- International Application: PCT/US2019/025020 2019.03.29
- International Announcement: WO2019/191697A 2019.10.03
- Date entered country: 2020-09-25
- Main IPC: G06T7/11
- IPC: G06T7/11 ; G16H70/60 ; G16H30/20 ; G16H30/40 ; G06N3/08 ; G06F18/214 ; G06V10/764 ; G06V10/82

Abstract:
A deep learning-based digital staining method and system are disclosed that enables the creation of digitally/virtually-stained microscopic images from label or stain-free samples based on autofluorescence images acquired using a fluorescent microscope. The system and method have particular applicability for the creation of digitally/virtually-stained whole slide images (WSIs) of unlabeled/unstained tissue samples that are analyzes by a histopathologist. The methods bypass the standard histochemical staining process, saving time and cost. This method is based on deep learning, and uses, in one embodiment, a convolutional neural network trained using a generative adversarial network model to transform fluorescence images of an unlabeled sample into an image that is equivalent to the brightfield image of the chemically stained-version of the same sample. This label-free digital staining method eliminates cumbersome and costly histochemical staining procedures and significantly simplifies tissue preparation in pathology and histology fields.
Public/Granted literature
- US20210043331A1 METHOD AND SYSTEM FOR DIGITAL STAINING OF LABEL-FREE FLUORESCENCE IMAGES USING DEEP LEARNING Public/Granted day:2021-02-11
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