Doctoral course - Polarimetric techniques combined with machine learning algorithms for biomedical diagnosis of tissue
Event information
Time
-
Location
Lecturer
Tatiana Novikova, PhD, Dr Habil (Ecole polytechnique, IP Paris, Palaiseau, France)
Schedule
- 6 hours lectures
- 6 office hours
- 2 hours exams
Monday 11.3 in TS133 at 9:00-17:00
Tuesday 12.3 in TS136 at 9:00-17:00
Wednesday 13.3 in TS287 at 10:30-11:00
Assessment
Attendance and exams (Pass/Fail)
Course Abstract
The studies of polarized light interaction with biological tissue may provide valuable information about the tissue pathological status. The basic advantage of polarimetric techniques consists in being relatively low-cost, fast and non-destructive, thus allowing the measurements even for in-situ applications. Recent advances of imaging Mueller polarimetry demonstrated its potential for early and accurate medical diagnosis of various diseases. Having access to the complete set of polarimetric data, namely, multi-spectral Mueller matrices proves to be the key issue for the accurate characterization of tissue samples. Post-processing of tissue polarimetric images combined with the machine learning algorithms can provide the quantitative diagnostic metric and complement the standard medical practice of tissue diagnosis.
Learning Objectives
- Introduction to the theoretical framework for the description of fully polarized and partially polarized light
- Getting familiar with the design, calibration and operation of imaging Mueller polarimeters in either reflection or transmission mode
- Understanding of non-linear Mueller matrix decomposition algorithms
- Practical examples of biomedical applications of imaging Mueller polarimetry
- optical biopsy of bulk tissue (colon, uterine cervix, brain)
- digital histology of tissue thin sections with transmission Mueller microscopy
- Machine learning algorithms for diagnostic segmentation of polarimetric images
Schedule
Day 1
9:00 – 10:30 Theoretical Stokes-Mueller formalism for the description of fully polarized and partially polarized light
10:30 – 10:45 Break
10:45 – 12:15 Design, calibration and operation of imaging Mueller polarimeters. Mueller matrix decomposition algorithms
12:15 – 13:15 Lunch
13:15 – 14:45 Biomedical applications of imaging Mueller polarimetry - optical biopsy of bulk tissue and digital histology of tissue thin sections
14:45 – 15:00 Break
15:00 – 16:30 Partial Mueller polarimetry. Machine learning algorithms for diagnostic segmentation of polarimetric images
Day 2
9:00 – 10:30 Office hours
10:30 – 10:45 Break
10:45 – 12:15 Office hours
12:15 – 13:15 Lunch
13:15 – 14:45 Office hours
14:45 – 15:00 Break
15:00 – 16:30 Office hours
Day 3
10:30 – 11:00 Exams
About the Instructor
Dr. Habil. Tatiana Novikova, Fellow of SPIE and Optica, leads the Characterisation and Modeling Division at the Laboratory of Physics of Interfaces and Thin Films, CNRS, Ecole polytechnique, IP Paris, France. She is a Courtesy Professor of the Department of Biomedical Engineering, Florida International University, Miami, USA. Dr Novikova published more than 100 peer-reviewed articles on optical polarization, Mueller polarimetry, biomedical imaging, polarimetric instrumentation, optical metrology and numerical modeling of electromagnetic wave interaction with structured and random media. Dr Novikova is an Editorial Board member of SPIE Journal of Biomedical Optics. She is a recipient of 2020 SPIE G. G. Stokes Award in optical polarization and 2023 European Optical Society Prize Winner.