US 2022/0036139 A1 · GPU ACCELERATED PERFUSION ESTIMATION FROM MULTISPECTRAL VIDEOS

Abstract

In an approach for classifying regions of tissue captured in multispectral videos into medically meaningful classes using GPU accelerated perfusion estimation, a processor receives one or more multispectral videos of a subject tissue of a patient. A processor extracts one or more fluorescence time series profiles from the one or more multispectral videos. A processor estimates one or more sets of perfusion parameters based on the one or more fluorescence time series profiles. A processor inputs one or more feature vectors into a classifier, wherein the one or more feature vectors are derived the one or more sets of perfusion parameters. A processor receives a classification result for each of the one or more feature vectors, wherein the classification result comprises a set of medically relevant labels for each of the one or more feature vectors with a level of certainty for each label of the set of medically relevant labels.

Claims20

Dependent claims

A computer-implemented method comprising:

receiving, by one or more processors, a set of inputs, wherein the set of inputs includes one or more multispectral videos of a subject tissue of a patient;
extracting, by the one or more processors, one or more fluorescence time series profiles from the one or more multispectral videos;
estimating, by the one or more processors, one or more sets of perfusion parameters based on the one or more fluorescence time series profiles;
inputting, by the one or more processors, one or more feature vectors into a classifier, wherein the one or more feature vectors are derived the one or more sets of perfusion parameters;
and
receiving, by the one or more processors, a classification result output by the classifier for each of the one or more feature vectors, wherein the classification result comprises a set of medically relevant labels for each of the one or more feature vectors with a level of certainty for each label of the set of medically relevant labels.

3 more elements

A computer program product comprising:

one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising:
program instructions to receive a set of inputs, wherein the set of inputs includes one or more multispectral videos of a subject tissue of a patient;
program instructions to extract one or more fluorescence time series profiles from the one or more multispectral videos;
program instructions to estimate one or more sets of perfusion parameters based on the one or more fluorescence time series profiles;
program instructions to input one or more feature vectors into a classifier, wherein the one or more feature vectors are derived the one or more sets of perfusion parameters;
and
program instructions to receive a classification result output by the classifier for each of the one or more feature vectors, wherein the classification result comprises a set of medically relevant labels for each of the one or more feature vectors with a level of certainty for each label of the set of medically relevant labels.

4 more elements

A computer system comprising:

one or more computer processors;
one or more computer readable storage media;
program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising:
program instructions to program instructions to receive a set of inputs, wherein the set of inputs includes one or more multispectral videos of a subject tissue of a patient;
program instructions to extract one or more fluorescence time series profiles from the one or more multispectral videos;
program instructions to estimate one or more sets of perfusion parameters based on the one or more fluorescence time series profiles;
program instructions to input one or more feature vectors into a classifier, wherein the one or more feature vectors are derived the one or more sets of perfusion parameters;
and
program instructions to receive a classification result output by the classifier for each of the one or more feature vectors, wherein the classification result comprises a set of medically relevant labels for each of the one or more feature vectors with a level of certainty for each label of the set of medically relevant labels.

6 more elements

Dependencies are inferred from the claim text.

Gpu accelerated perfusion estimation from multispectral videos

Life of this patent

Gpu accelerated perfusion estimation from multispectral videos

Life of this patent

Abstract

Claims20