Robust 3D reconstruction and identification of dendritic spines from optical microscopy imaging.
In neurobiology, the 3D reconstruction of neurons followed by the identification of dendritic spines is essential for studying neuronal morphology, function and biophysical properties. Most existing methods suffer from problems of low reliability, poor accuracy and require much user interaction. In this paper, we present a method to reconstruct dendrites using a surface representation of the neuron. The skeleton of the dendrite is extracted by a procedure based on the medial geodesic function that is robust and topology preserving, and it is used to accurately identify spines. The sensitivity of the algorithm on the various parameters is explored in detail and the method is shown to be robust.
Janoos
Firdaus
F
Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA. janoos@cse.ohio-state.edu
Mosaliganti
Kishore
K
Xu
Xiaoyin
X
Machiraju
Raghu
R
Huang
Kun
K
Wong
Stephen T C
ST
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D002478:Cells, Cultured; D049229:Dendritic Spines / Q000648:ultrastructure*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D036641:Microscopy, Fluorescence, Multiphoton / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D051381:Rats; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity