Full field strain mapping of collagenous tissue typically uses fiducial markers; however, fiducial markers have limited spatial resolution and obstruct light traveling to the sensor when used in conjunction with optical techniques such as Quantitative Polarized Light Imaging (QPLI) [1]. To overcome the limitations of fiducial markers, Quinn et al. proposed a new optical strain tracking method for QPLI that relies on image texture that arises from polarimetry outcomes to calculate strain [1]. Using a modified definition of correlation, image texture generated from QPLI data was tracked between frames to measure deformation. Based on their pseudocode, we implemented the strain mapping algorithm in Python and validated it on a set of control QPLI phantom videos. Future work will extend this algorithm to use of experimental QPLI data; the present state of our implementation struggles to track image texture in videos with low temporal resolution and videos where the signal strength was weak.

Document Type

Final Report

Author's School

McKelvey School of Engineering

Author's Department

Mechanical Engineering and Materials Science

Class Name

Mechanical Engineering and Material Sciences Independent Study

Date of Submission