[2I4-GS-10] AI application: detection

[2I4-GS-10-03] Proposal of cell protrusion detection by rule-based approach and its quantitative evaluation

〇Fumiya Chikudo¹, BAAR STEFAN¹, Kiyotaka Tokuraku¹, Masahiro Kuragano¹, Ayaka Ota¹, Shinya Watanabe¹ (1. Muroran Institute of Technology)

Keywords:Cell protrusion, Quantitative evaluation, Image analysis

Nerve cells are composed of cell bodies and neurites, and it is known that most of the motor functions of cells are produced by the expansion and contraction of neurites. Therefore, in order to estimate the degree of activity and motor function of the cells themselves, it is necessary to perform a detailed analysis focusing on the neurites. However, it is difficult to define the neurite region strictly, and in many cases, it is judged by the human eye, so there is a problem that only subjective and non-quantitative evaluation can be performed. Therefore, in this study, we attempted to realize a more quantitative and objective evaluation method focusing on the protrusion region by mechanically detecting the protrusion region by utilizing the rule-based approach. Specifically, polar coordinate transformation was applied to the masked cell image, and the protrusion region was automatically detected by defining the protrusion region from the unevenness of the polar coordinate graph. As a result of simulation experiments on some annotated mask data, it was confirmed that appropriate protrusion detection and quantitative evaluation of protrusion movement based on the detection results were performed.