TY - GEN
T1 - Rapid semi-automated segmentation and analysis of neuronal morphology and function from confocal image data
AU - Holmes, David R.
AU - Moore, Michael J.
AU - Mantilla, Carlos B.
AU - Sieck, Gary C.
AU - Robb, Richard A.
N1 - Publisher Copyright:
© 2002 IEEE.
PY - 2002
Y1 - 2002
N2 - Confocal microscopy combined with cellular labeling techniques can be an effective method for imaging the morphology of a cell as well as various functional characteristics in vivo. Current analysis methods are manual, and therefore, time-consuming and prone to error. Through the development of custom algorithms and application design, the analysis process can be improved to decrease analysis time and increase reproducibility. Utilizing off-the-self PC hardware and software, a custom application was designed that would provide useful three-dimensional (3D) segmentation and analysis tools to analyze confocal image data of neurons. Techniques such as dynamic thresholding, adaptive filtering, and morphological processing were implemented to provide a robust and efficient analysis package. The automated method was compared with the standard manual method using two metrics - reproducibility and overall time necessary for analysis. The semi-automated method was more time efficient with very high reproducibility. Additional studies are necessary to further assess and improve upon the automated technique.
AB - Confocal microscopy combined with cellular labeling techniques can be an effective method for imaging the morphology of a cell as well as various functional characteristics in vivo. Current analysis methods are manual, and therefore, time-consuming and prone to error. Through the development of custom algorithms and application design, the analysis process can be improved to decrease analysis time and increase reproducibility. Utilizing off-the-self PC hardware and software, a custom application was designed that would provide useful three-dimensional (3D) segmentation and analysis tools to analyze confocal image data of neurons. Techniques such as dynamic thresholding, adaptive filtering, and morphological processing were implemented to provide a robust and efficient analysis package. The automated method was compared with the standard manual method using two metrics - reproducibility and overall time necessary for analysis. The semi-automated method was more time efficient with very high reproducibility. Additional studies are necessary to further assess and improve upon the automated technique.
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U2 - 10.1109/ISBI.2002.1029236
DO - 10.1109/ISBI.2002.1029236
M3 - Conference contribution
AN - SCOPUS:12444341516
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 233
EP - 236
BT - 2002 IEEE International Symposium on Biomedical Imaging, ISBI 2002 - Proceedings
PB - IEEE Computer Society
T2 - IEEE International Symposium on Biomedical Imaging, ISBI 2002
Y2 - 7 July 2002 through 10 July 2002
ER -