TY - JOUR
T1 - SpineLab
T2 - Tool for three-dimensional reconstruction of neuronal cell morphology
AU - Jungblut, Daniel
AU - Vlachos, Andreas
AU - Schuldt, Gerlind
AU - Zahn, Nadine
AU - Deller, Thomas
AU - Wittum, Gabriel
N1 - Funding Information:
We thank Sergei Wolf from G-CSC Frankfurt for creating the model neurons with NeuGen. The work was supported by a German-Israeli Foundation Grant (GIF G-2239-2096.1/2009), by Deutsche Forschungsgemeinschaft DFG (DE551/10-1;11-1), by BMBF via Bernstein-Group DMSPiN and by Baden-Württemberg-Stiftung via project HPC-12.
PY - 2012/7
Y1 - 2012/7
N2 - SpineLab is a software tool developed for reconstructing neuronal feature skeletons from three-dimensional single-or multi-photon image stacks. These images often suffer from limited resolution and a low signal-to-noise ratio, making the extraction of morphometric information difficult. To overcome this limitation, we have developed a software tool that offers the possibility to create feature skeletons in various modes-automatically as well as with manual interaction. We have named this novel tool SpineLab. In a first step, an investigator adjusts a set of parameters for automatic analysis in an interactive manner, i.e., with online visual feedback, followed by a second step, in which the neuronal feature skeleton can be modified by hand. We validate the ability of SpineLab to reconstruct the entire dendritic tree of identified GFP-expressing neurons and evaluate the accuracy of dendritic spine detection. We report that SpineLab is capable of significantly facilitating the reconstruction of dendrites and spines. Moreover, the automatic approach appears sufficient to detect spine density changes in time-lapse imaging experiments. Taken together, we conclude that SpineLab is an ideal software tool for partially automatic reconstruction of neural cell morphology.
AB - SpineLab is a software tool developed for reconstructing neuronal feature skeletons from three-dimensional single-or multi-photon image stacks. These images often suffer from limited resolution and a low signal-to-noise ratio, making the extraction of morphometric information difficult. To overcome this limitation, we have developed a software tool that offers the possibility to create feature skeletons in various modes-automatically as well as with manual interaction. We have named this novel tool SpineLab. In a first step, an investigator adjusts a set of parameters for automatic analysis in an interactive manner, i.e., with online visual feedback, followed by a second step, in which the neuronal feature skeleton can be modified by hand. We validate the ability of SpineLab to reconstruct the entire dendritic tree of identified GFP-expressing neurons and evaluate the accuracy of dendritic spine detection. We report that SpineLab is capable of significantly facilitating the reconstruction of dendrites and spines. Moreover, the automatic approach appears sufficient to detect spine density changes in time-lapse imaging experiments. Taken together, we conclude that SpineLab is an ideal software tool for partially automatic reconstruction of neural cell morphology.
KW - Dendritic tree
KW - Graphical user interface
KW - Morphology reconstruction
KW - Neuronal feature skeleton
KW - Neurons
KW - Spine density changes
KW - SpineLab-software
KW - Spines
UR - http://www.scopus.com/inward/record.url?scp=84872008695&partnerID=8YFLogxK
U2 - 10.1117/1.JBO.17.7.076007
DO - 10.1117/1.JBO.17.7.076007
M3 - Article
C2 - 22894490
AN - SCOPUS:84872008695
SN - 1083-3668
VL - 17
JO - Journal of biomedical optics
JF - Journal of biomedical optics
IS - 7
M1 - 076007
ER -