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 10):
The method as recited in  claim 9 , wherein the programmable gate array includes at least one of the following: a PLA and an FPGA.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 1.53165
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15016217', '15263419', '13181150', '15672051', '13109640']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2782902174571462
- 35 USC 102 Novelty (BERT): 0.4885512992857611
- Combined Prediction Score: 0.2993163256400077
- Mean Citation Score: 126.8900548
- Max Citation Score: 153.82976000000005
- Similarity Product: 103.7183780375672

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