Fuzzy logic based detection of neuron bifurcations in microscopy images
Quantitative analysis of neuronal cell morphology from microscopic image data requires accurate reconstruction of the axonal and dendritic trees. The most critical points to be detected in this process are the bifurcations. Here we present a new method for fully automatic detection of bifurcations in microscopic images. The proposed method models the essential characteristics of bifurcations and employs fuzzy rule based reasoning to decide whether the extracted image features indicate the presence of a bifurcation. Algorithm tests on synthetic image data show high noise immunity and experiments with real fluorescence microscopy data exhibit average recall and precision of 90.4% and 90.5% respectively.
|Bifurcation detection, Fluorescence microscopy, Fuzzy logic, Neuron reconstruction|
|2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014|
|Organisation||Department of Biomedical Engineering|
Radojević, M, Smal, I, Niessen, W.J, & Meijering, H.W. (2014). Fuzzy logic based detection of neuron bifurcations in microscopy images. Presented at the 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014. Retrieved from http://hdl.handle.net/1765/90612