Advanced methodology useful for exploring distortions in confocal microscopy medical images: Application to neurodegenerative pathology

Abstract

Alzheimer's disease is a neurodegenerative disease that primarily affects the nervous system and is characterized by a progressive loss of nerve cells. In order to understand and explore such pathology, confocal microscope images could be widely used because of their interesting high clarity in term of cell identification. In fact, confocal microscopy is a potential tool that enables real-time imaging of living tissue at high resolution and high contrast. However, in practical microscopy, aberration-free confocal imaging is rarely achieved. So, aberration corrected images of biological specimens show considerable improvement. Geometric aberrations are considered as the main sources of image degradation. The purpose of this project was to develop an advanced method that is able to estimate the distortion parameters and to test these parameters to correct image deformations. Such method was based on the adaptation of the Zhang's algorithm implemented in the OpenCV library in order to calibration of confocal microscopy images and results of simulation were interesting and promoting and could involve other research areas such as stitching confocal microscopic images and working in high resolution.