A tool for automatic dendritic spine detection and analysis. Part I: Dendritic spine detection using multi-level region-based segmentation

We propose an image processing pipeline for dendritic spine detection in two-photon fluorescence microscopy images. Spines of interest to neuroscientists often contain high intensity regions with respect to their surroundings. We find such maxima regions using morphological image reconstruction. The...

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Bibliographic Details
Published in2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA) pp. 167 - 171
Main Authors Erdil, E., Yagci, A. M., Argunsah, A. O., Ramiro-Cortes, Y., Hobbiss, A. F., Israely, I., Unay, D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
Biomedical imaging
clustering
dendritic spines
Filtering
fluorescence microscopy
Image reconstruction
Image segmentation
Neural image processing
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Summary:We propose an image processing pipeline for dendritic spine detection in two-photon fluorescence microscopy images. Spines of interest to neuroscientists often contain high intensity regions with respect to their surroundings. We find such maxima regions using morphological image reconstruction. These regions facilitate a multi-level segmentation algorithm to detect spines. First, watershed algorithm is applied to extract initial rough regions of spines. Then, these results are further refined using a graph-theoretic region-growing algorithm which incorporates segmentation on a sparse representation of image data and hierarchical clustering as a post-processing step. We compare our final results to segmentation results of the domain expert. Our pipeline produces promising segmentation results with practical run times for monitoring streaming data.
ISBN:9781467325851
1467325856
ISSN:2154-5111
2154-512X
DOI:10.1109/IPTA.2012.6469558