Medical applications of laser molecular imaging and machine learning / Yury V. Kistenev, Alexey V. Borisov, Denis A. Vrazhnov.

Format:

Book

Author/Creator:

Kistenev, Yury V., author.

Borisov, A. V. (Alekseĭ Vladimirovich), author.

Vrazhnov, Denis A., author.

Contributor:

Society of Photo-Optical Instrumentation Engineers, publisher.

Series:

SPIE monograph ; PM333.

SPIE Press monograph ; PM333

Language:

English

Subjects (All):

Molecular diagnosis.

Machine learning.

Lasers in medicine.

Molecular Imaging.

Machine Learning.

Optics and Photonics.

Medical Subjects:

Molecular Imaging.

Machine Learning.

Optics and Photonics.

Physical Description:

1 online resource (xiii, 252 pages) : illustrations.

Place of Publication:

Bellingham, Washington : SPIE, 2021.

System Details:

Mode of access: World Wide Web.

Summary:

This book examines various biophotonics applications associated with modern machine learning techniques and laser molecular imaging and spectroscopy. Most of the existing books focus on either a specific instrumental method, such as terahertz and IR spectroscopy or Raman scattering, or a limited number of mathematical tools for raw data analysis. We describe a thorough review of molecular imaging technologies and current machine learning approaches to perform data analysis of gaseous, liquid samples of biological origin and biotissues. Much of the material highlights applications of machine learning to develop non-invasive medical diagnostics tools.

Contents:

Preface

List of acronyms and abbreviations

1. Fundamental concepts related to laser molecular imaging: Introduction; 1.1. Molecular biomarkers; 1.2. Basics of laser molecular spectroscopy and imaging; 1.3. Basics of machine learning; Conclusion; References

2. Laser-based molecular data-acquisition technologies: Introduction; 2.1. Data-acquisition technologies suitable for breath biopsy; 2.2. Data acquisition technologies suitable for optical liquid biopsy; 2.3. Data acquisition technologies suitable for optical tissue biopsy; Conclusion; References

3. Informative feature extraction: Introduction; 3.1. Feature selection; 3.2. Feature extraction; 3.3. Outliers and noise reduction; Conclusion; References

4. Clusterization and predictive model construction: Introduction; 4.1. Unsupervised learning methods: clusterization; 4.2. Predictive model construction; Conclusion; References

5. Medical applications: Introduction; 5.1. Breath optical biopsy by laser absorption spectroscopy and machine learning; 5.2. Liquid optical biopsy by IR and THz laser spectroscopy and machine learning; 5.3. Tissue optical biopsy using laser molecular imaging and machine learning; Conclusion; References

Supplemental materials

Index.

Notes:

"SPIE Digital Library."--Website.

Includes bibliographical references and index.

Title from PDF title screen (SPIE eBooks Website, viewed 2021-08-02).

Other Format:

Print version:

ISBN:

9781510645356

OCLC:

1262898682

Access Restriction:

Restricted for use by site license.