Convolutional Neural Networks-Based Image Analysis for the Detection and Quantification of Neutrophil Extracellular Traps.

ABSTRACT: Over a decade ago, the formation of neutrophil extracellular traps (NETs) was described as a novel mechanism employed by neutrophils to tackle infections. Currently applied methods for NETs release quantification are often limited by the use of unspecific dyes and technical difficulties. Therefore, we aimed to develop a fully automatic image processing method for the detection and quantification of NETs based on live imaging with the use of DNA-staining dyes. For this purpose, we adopted a recently proposed Convolutional Neural Network (CNN) model called Mask R-CNN. The adopted model detected objects with quality comparable to manual counting-Over 90% of detected cells were classified in the same manner as in manual labelling. Furthermore, the inhibitory effect of GW 311616A (neutrophil el

SUBMITTER: Manda-Handzlik A 

PROVIDER: S-EPMC7072771 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature