Automatic detection, segmentation and characterization of retinal horizontal neurons in large-scale 3D confocal imagery

Mahmut Karakaya; Ryan A. Kerekes; Shaun S. Gleason; Rodrigo A. P. Martins; Michael A. Dyer

doi:10.1117/12.878029

14 March 2011 Automatic detection, segmentation and characterization of retinal horizontal neurons in large-scale 3D confocal imagery

Mahmut Karakaya, Ryan A. Kerekes, Shaun S. Gleason, Rodrigo A. P. Martins, Michael A. Dyer

Author Affiliations +

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79622J (2011) https://doi.org/10.1117/12.878029
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Automatic analysis of neuronal structure from wide-field-of-view 3D image stacks of retinal neurons is essential for statistically characterizing neuronal abnormalities that may be causally related to neural malfunctions or may be early indicators for a variety of neuropathies. In this paper, we study classification of neuron fields in large-scale 3D confocal image stacks, a challenging neurobiological problem because of the low spatial resolution imagery and presence of intertwined dendrites from different neurons. We present a fully automated, four-step processing approach for neuron classification with respect to the morphological structure of their dendrites. In our approach, we first localize each individual soma in the image by using morphological operators and active contours. By using each soma position as a seed point, we automatically determine an appropriate threshold to segment dendrites of each neuron. We then use skeletonization and network analysis to generate the morphological structures of segmented dendrites, and shape-based features are extracted from network representations of each neuron to characterize the neuron. Based on qualitative results and quantitative comparisons, we show that we are able to automatically compute relevant features that clearly distinguish between normal and abnormal cases for postnatal day 6 (P6) horizontal neurons.

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Mahmut Karakaya, Ryan A. Kerekes, Shaun S. Gleason, Rodrigo A. P. Martins, and Michael A. Dyer "Automatic detection, segmentation and characterization of retinal horizontal neurons in large-scale 3D confocal imagery", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79622J (14 March 2011); https://doi.org/10.1117/12.878029

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