PATENT CLAIM ANALYSIS

Application Number: 15928992
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-10
Patent Classification: ["382", "128000"]

Abstract:
A method and apparatus for using deep learning in label-free cell classification and machine vision extraction of particles. A time stretch quantitative phase imaging (TS-QPI) system is described which provides high-throughput quantitative imaging, and utilizing photonic time stretching. In at least one embodiment, TS-QPI is integrated with deep learning to achieve record high accuracies in label-free cell classification. The system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. The system is particularly well suited for data-driven phenotypic diagnosis and improved understanding of heterogeneous gene expression in cells.

Claim (Index 24):
A particle sorting apparatus, the apparatus comprising:\n an optical path having a plurality of optical elements toward a particle sorting field of view and characterized as having different path lengths for different wavelengths of light; an optical pulse generator that directs a plurality of optical pulses along the optical path, each pulse comprising multiple wavelengths of light and incident on target particles within the particle sorting field of view; a time-stretch amplifier that converts return optical pulses from the target particles into time-stretched optical pulses according to wavelengths of light in the return optical pulse; an optical sensor that converts the time-stretched optical pulses into a digital interferogram that includes optical phase and information loss associated with at least one of the target particles; a particle feature extractor that extracts particle features from the digital interferogram; and a classification module that classifies the target particles according to known classes defined based on known particle features that are derived based on known optical phase and known information loss, and as a function of the target particle features.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 1.53165
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15016217', '15263419', '13181150', '15672051', '13109640']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.259614677466559
- 35 USC 102 Novelty (BERT): 0.46392757432041
- Combined Prediction Score: 0.2800459671519441
- Mean Citation Score: 126.8900548
- Max Citation Score: 153.82976000000005
- Similarity Product: 124.04399087238316

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test