کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4334922 1614623 2015 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Quantitative 3-D analysis of GFAP labeled astrocytes from fluorescence confocal images
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
Quantitative 3-D analysis of GFAP labeled astrocytes from fluorescence confocal images
چکیده انگلیسی


• Quantitative 3-D profiling of brain astrocytes from confocal fluorescence images.
• Useful for quantitative studies of astrocytes in health, injury, and disease.
• Identifies astrocyte nuclei and generates 3-D arbor reconstructions.
• Produces comprehensive arbor measurements.
• Performs a harmonic co-clustering of the cell population.
• Uses machine-learning to cope with biological and imaging variability.

BackgroundThere is a need for effective computational methods for quantifying the three-dimensional (3-D) spatial distribution, cellular arbor morphologies, and the morphological diversity of brain astrocytes to support quantitative studies of astrocytes in health, injury, and disease.New methodConfocal fluorescence microscopy of multiplex-labeled (GFAP, DAPI) brain tissue is used to perform imaging of astrocytes in their tissue context. The proposed computational method identifies the astrocyte cell nuclei, and reconstructs their arbors using a local priority based parallel (LPP) tracing algorithm. Quantitative arbor measurements are extracted using Scorcioni's L-measure, and profiled by unsupervised harmonic co-clustering to reveal the morphological diversity.ResultsThe proposed method identifies astrocyte nuclei, generates 3-D reconstructions of their arbors, and extracts quantitative arbor measurements, enabling a morphological grouping of the cell population.Comparison with existing methodsOur method enables comprehensive spatial and morphological profiling of astrocyte populations in brain tissue for the first time, and overcomes limitations of prior methods. Visual proofreading of the results indicate a >95% accuracy in identifying astrocyte nuclei. The arbor reconstructions exhibited 3.2% fewer erroneous jumps in tracing, and 17.7% fewer false segments compared to the widely used fast-marching method that resulted in 9% jumps and 20.8% false segments.ConclusionsThe proposed method can be used for large-scale quantitative studies of brain astrocyte distribution and morphology.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 246, 15 May 2015, Pages 38–51
نویسندگان
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