Back to results
US 11,079,279 B2Granted
Diagnosis method using laser induced breakdown spectroscopy and diagnosis device performing the same
AssigneeSpeclipse, Inc.
InventorsSung Hyun Pyun, Wan Ki Min
Life of this patent
Estimating the term…
Abstract
Disclosed herein are a diagnostic method using laser induced breakdown spectrum analysis and a diagnostic device for performing the same. The diagnostic method may include projecting a pulsed laser to a suspicious specimen, obtaining first spectrum data on the light collected from the suspicious specimen, projecting the pulsed laser to a non-diseased specimen, obtaining second spectrum data on the light collected from the non-diseased specimen, and determining whether a disease is present in the suspicious specimen from a comparison value of the first spectrum data and the second spectrum data using an artificial neural network.
Claims20
A method for diagnosing a disease of a patient by using Laser-Induced Breakdown Spectroscopy (LIBS), the method comprising:
- projecting a first pulsed laser beam to a suspicious tissue to induce plasma ablation at the suspicious tissue of the patient;
- receiving first light generated by the plasma ablation induced at the suspicious tissue;
- obtaining first spectrum data related to the first light;
- projecting a second pulsed laser beam to a reference tissue to induce plasma ablation at the reference tissue of the patient;
- receiving second light generated by the plasma ablation induced at the reference tissue;
- obtaining second spectrum data related to the second light;
- and
- determining whether the suspicious tissue is a disease tissue based on an output of an artificial neural network to which input data including comparison data of the first spectrum data and the second spectrum data is inputted,
- wherein the artificial neural network has been trained with training-data set including first data and second data, the first data includes first comparison data of two spectrum data related to light generated by plasma ablation induced respectively at two different non-disease tissues of a single subject and the second data includes second comparison data of two spectrum data related to light generated by plasma ablation induced respectively at a non-disease tissue and a disease tissue of a single subject, and
- wherein the first data is labeled with a first class value indicating normal status and the second data is labeled with a second class value indicating disease status.
7 more elements
A method for diagnosing a disease of a patient by using Laser-Induced Breakdown Spectroscopy (LIBS), the method comprising:
- obtaining first spectrum data related to first light generated by plasma ablation induced at a target tissue of the patient;
- obtaining second spectrum data related to second light generated by plasma ablation induced at a reference tissue of the patient;
- and
- determining whether the target tissue is a disease tissue based on an output of an artificial neural network to which input data including comparison data of the first spectrum data and the second spectrum data is inputted,
- wherein the artificial neural network has been trained with a training-data set including first data and second data, the first data includes first comparison data of two spectrum data related to light generated by plasma ablation induced respectively at two different non-disease tissues of a single subject and the second data includes second comparison data of two spectrum data related to light generated by plasma ablation induced respectively at a non-disease tissue and a disease tissue of a single subject, and
- wherein the first data is labeled with a first class value indicating normal status and the second data is labeled with a second class value indicating disease status.
3 more elements
A diagnostic device comprising:
- a laser projection module configured to project a pulsed laser beam to a tissue for inducing plasma ablation;
- a light receiving module configured to receive light generated by the plasma ablation induced at the tissue by the pulsed laser beam, wherein the light generated by the plasma ablation includes continuum emission light having continuous spectrum characteristic and element specific emission light having discontinuous spectrum characteristic;
- a spectrum measurement module configured to obtain spectrum data from the received light;
- and
- a controller configured to:
- obtain first spectrum data related to first light generated by the first plasma ablation induced at a target tissue,
- obtain second spectrum data related to second light generated by second plasma ablation induced at a reference tissue, and
- determine whether the target tissue is a disease tissue based on an output of an artificial neural network to which input data including comparison data of the first spectrum data and the second spectrum data is inputted,
- wherein the artificial neural network has been trained with a training-data set including first data and second data, the first data includes first comparison data of two spectrum data related to light generated by plasma ablation induced respectively at two different non-disease tissues of a single subject and the second data includes second comparison data of two spectrum data related to light generated by plasma ablation induced respectively at a non-disease tissue and a disease tissue of a single subject, and
- wherein the first data is labeled with a first class value indicating normal status and the second data is labeled with a second class value indicating disease status.
7 more elements
Dependencies are inferred from the claim text.