Invention Publication
- Patent Title: METHOD AND SYSTEM FOR DIGITAL STAINING OF LABEL-FREE FLUORESCENCE IMAGES USING DEEP LEARNING
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Application No.: US18543168Application Date: 2023-12-18
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Publication No.: US20240135544A1Publication Date: 2024-04-25
- 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
- Main IPC: G06T7/11
- IPC: G06T7/11 ; G06F18/214 ; G06N3/08 ; G06V10/764 ; G06V10/82 ; G16H30/20 ; G16H30/40 ; G16H70/60

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.
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