US 2026/0219108 A1 · SYSTEMS AND METHODS TO ANALYZE SPECTROSCOPY DATA FOR MULTI-PATHOGEN DETECTION AND IDENTIFICATION

Abstract

A non-transitory, processor-readable medium stores instructions that, when executed by a processor, cause the processor to provide Raman spectrum data as input to a 1-dimensional encoder to identify a feature of the Raman spectrum data. The instructions further cause the processor to provide hyperspectral image data as input to a 2-dimensional+1-dimesional encoder to identify a feature of the hyperspectral image data. Cross-modal attention is performed to (1) analyze, based on the feature of the Raman spectrum data, a region represented by the hyperspectral image data to identify a refined feature of the hyperspectral image data and (2) analyze, based on the feature of the hyperspectral image data, a peak represented by the Raman spectrum data to identify a refined feature of the Raman spectrum data. A type associated with a sample is classified based on the refined features of the hyperspectral image data and Raman spectrum data.

Claims20

Dependent claims

A non-transitory, processor-readable medium storing instructions that, when executed by a processor, cause the processor to:

provide Raman spectrum data associated with a sample as input to a 1-dimensional encoder to identify a feature of the Raman spectrum data;
provide hyperspectral image data associated with the sample as input to a 2-dimensional+1-dimesional encoder to identify a feature of the hyperspectral image data;
perform cross-modal attention to (1) analyze, based on the feature of the Raman spectrum data, a region represented by the hyperspectral image data to identify a refined feature of the hyperspectral image data and (2) analyze, based on the feature of the hyperspectral image data, a peak represented by the Raman spectrum data to identify a refined feature of the Raman spectrum data;
and
classify a type associated with the sample based on (1) the refined feature of the hyperspectral image data and (2) the refined feature of the Raman spectrum data.

2 more elements

A method, comprising:

providing, via a processor, first spectrum data associated with (1) a pathogen and (2) a first spectrum type as input to a 1-dimensional encoder to identify a feature of the first spectrum data;
providing, via the processor, second spectrum data associated with (1) the pathogen (2) a second spectrum type different from the first spectrum type as input to a 2-dimensional+1-dimesional encoder to identify a feature of the second spectrum data;
performing, via the processor, cross-modal attention to (1) analyze, based on the feature of the first spectrum data, a region represented by the second spectrum data to identify a refined feature of the second spectrum data and (2) analyze, based on the feature of the second spectrum data, a peak represented by the first spectrum data to identify a refined feature of the first spectrum data;
and
classifying, via the processor, a cell type associated with the pathogen based on (1) the refined feature of the first spectrum data and (2) the refined feature of the second spectrum data.

2 more elements

Dependencies are inferred from the claim text.

Systems and methods to analyze spectroscopy data for multi-pathogen detection and identification

Life of this patent

Systems and methods to analyze spectroscopy data for multi-pathogen detection and identification

Life of this patent

Abstract

Claims20