Abstract
Advances in imaging technology have enabled observation of various biological phenomena at the nanoscale resolution, which was previously not possible. However, extracting useful information from such images to understand various phenomena is becoming increasingly difficult because of the complexity and large amount of data involved. Numerous computational techniques, such as classic signal processing filters using image processing software, and segmentation of region of interest using machine learning, have been proposed for image analysis. Thus, selecting an appropriate method according to research goals is critical. In this paper, we briefly review our image analysis methods and their related techniques applied for analysis of cell population and intracellular images acquired by the latest imaging technology. Our image analysis methods include noise reduction, dynamic analysis of cell population and microtubules, segmentation of cytoplasmic membrane, and cell division event detection.
