Invention Grant
- Patent Title: Method and system for detection and classification of cells using convolutional neural networks
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Application No.: US15690037Application Date: 2017-08-29
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Publication No.: US10282589B2Publication Date: 2019-05-07
- Inventor: Maral Mesmakhosroshahi , Shubham Agarwal , Yongmian Zhang
- Applicant: KONICA MINOLTA LABORATORY U.S.A., INC.
- Applicant Address: US CA San Mateo
- Assignee: KONICA MINOLTA LABORATORY U.S.A., INC.
- Current Assignee: KONICA MINOLTA LABORATORY U.S.A., INC.
- Current Assignee Address: US CA San Mateo
- Agency: Chen Yoshimura LLP
- Main IPC: G06K9/00
- IPC: G06K9/00 ; G06K9/62

Abstract:
An artificial neural network system implemented on a computer for cell segmentation and classification of biological images. It includes a deep convolutional neural network as a feature extraction network, a first branch network connected to the feature extraction network to perform cell segmentation, and a second branch network connected to the feature extraction network to perform cell classification using the cell segmentation map generated by the first branch network. The feature extraction network is a modified VGG network where each convolutional layer uses multiple kernels of different sizes. The second branch network takes feature maps from two levels of the feature extraction network, and has multiple fully connected layers to independently process multiple cropped patches of the feature maps, the cropped patches being located at a centered and multiple shifted positions relative to the cell being classified; a voting method is used to determine the final cell classification.
Public/Granted literature
- US20190065817A1 METHOD AND SYSTEM FOR DETECTION AND CLASSIFICATION OF CELLS USING CONVOLUTIONAL NEURAL NETWORKS Public/Granted day:2019-02-28
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