AI-based cell classification method and system
AssigneeVisiongate, Inc.
InventorMichael G. Meyer
Life of this patent
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Abstract
The present disclosure provides a system and method for AI-based cell classification of cells from a patient sample to determine if cells indicative of lung cancer are present. In the system and method, 2D imaging is used to eliminate cells not likely to be indicative of lung cancer from subsequent 3D imaging, while 3D imaging is conducted for cells likely to be indicative of lung cancer. The present disclosure further provides a method of training 2D cell classifiers for use in the system and method for AI-based cell classification.
Claims21
An artificial intelligence (AI)-based cell classification method comprising:
- a) generating, by an optical tomography system, a representative 2D image of a cell from a patient sample comprising a plurality of cells;
- b) evaluating the representative 2D image using an abnormal cell 2D artificial intelligence classifier to determine if the cell has abnormal features;
- c) evaluating the representative 2D image using a Bronchial Epithelial Cell (BEC) 2D artificial intelligence classifier to determine if the cell has Bronchial Epithelial Cell (BEC)-like features;
- and
- d) generating, by the optical tomography system, a 3D image of the cell if the cell is determined to have abnormal features or to have BEC-like features.
A cell classification system comprising:
- an optical tomography system operable to:
- generate a representative 2D image of a cell from a patient sample;
- and
- generate a 3D image of the cell if the cell has abnormal features or Bronchial Epithelial Cell (BEC)-like features;
- and
- a processor operable to:
- compare the representative 2D image of the cell to an abnormal cell 2D artificial intelligence classifier to determine if the cell has abnormal features;
- and
- compare the representative 2D image of the cell to a Bronchial Epithelial Cell (BEC) 2D artificial intelligence classifier to determine if the cell has BEC-like features.
Dependencies are inferred from the claim text.