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Object-based segmentation <t>of</t> <t>synaptic</t> puncta using <t>IMA</t> in MetaMorph software (A) A source image as confocal PSD95 image selected for specific objects based on length, breadth, and area filters. (B) A display of filtering parameters in IMA. (C) Object data for the synaptic puncta obtained through IMA. (D) A binary IMA object mask created as an output image. (E and F) Dynamic data exchange command for exporting the object data on postsynaptic puncta to an excel file.
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Image Search Results


Object-based segmentation of synaptic puncta using IMA in MetaMorph software (A) A source image as confocal PSD95 image selected for specific objects based on length, breadth, and area filters. (B) A display of filtering parameters in IMA. (C) Object data for the synaptic puncta obtained through IMA. (D) A binary IMA object mask created as an output image. (E and F) Dynamic data exchange command for exporting the object data on postsynaptic puncta to an excel file.

Journal: STAR Protocols

Article Title: Quantifying molecular aggregation by super resolution microscopy within an excitatory synapse from mouse hippocampal neurons

doi: 10.1016/j.xpro.2021.100470

Figure Lengend Snippet: Object-based segmentation of synaptic puncta using IMA in MetaMorph software (A) A source image as confocal PSD95 image selected for specific objects based on length, breadth, and area filters. (B) A display of filtering parameters in IMA. (C) Object data for the synaptic puncta obtained through IMA. (D) A binary IMA object mask created as an output image. (E and F) Dynamic data exchange command for exporting the object data on postsynaptic puncta to an excel file.

Article Snippet: Object-based segmentation of synaptic puncta using IMA in MetaMorph software (A) A source image as confocal PSD95 image selected for specific objects based on length, breadth, and area filters. (B) A display of filtering parameters in IMA. (C) Object data for the synaptic puncta obtained through IMA. (D) A binary IMA object mask created as an output image. (E and F) Dynamic data exchange command for exporting the object data on postsynaptic puncta to an excel file. g. Create ROIs on the filtered objects (refer above to step f).

Techniques: Software

Creating ROIs on the filtered objects in MetaMorph software (A) Region menu displaying several options like creating regions around objects or transferring regions from one image to another. (B) Creating ROIs around the objects filtered with IMA object mask as the source image. The ROIs are marked in yellow color.

Journal: STAR Protocols

Article Title: Quantifying molecular aggregation by super resolution microscopy within an excitatory synapse from mouse hippocampal neurons

doi: 10.1016/j.xpro.2021.100470

Figure Lengend Snippet: Creating ROIs on the filtered objects in MetaMorph software (A) Region menu displaying several options like creating regions around objects or transferring regions from one image to another. (B) Creating ROIs around the objects filtered with IMA object mask as the source image. The ROIs are marked in yellow color.

Article Snippet: Object-based segmentation of synaptic puncta using IMA in MetaMorph software (A) A source image as confocal PSD95 image selected for specific objects based on length, breadth, and area filters. (B) A display of filtering parameters in IMA. (C) Object data for the synaptic puncta obtained through IMA. (D) A binary IMA object mask created as an output image. (E and F) Dynamic data exchange command for exporting the object data on postsynaptic puncta to an excel file. g. Create ROIs on the filtered objects (refer above to step f).

Techniques: Software, Transferring

Semiautomated detection of functional zones (PSD) of an excitatory synapse using MetaMorph software (A and C) STED PSD95 image and a corresponding binary IMA object mask with regions created around objects segmented as PSD regions using IMA. The filtered PSDs are marked in green while the region boundaries are shown in yellow. (B and D) The IMA and thresholding parameters employed for filtering PSDs from STED PSD95 image as a source image.

Journal: STAR Protocols

Article Title: Quantifying molecular aggregation by super resolution microscopy within an excitatory synapse from mouse hippocampal neurons

doi: 10.1016/j.xpro.2021.100470

Figure Lengend Snippet: Semiautomated detection of functional zones (PSD) of an excitatory synapse using MetaMorph software (A and C) STED PSD95 image and a corresponding binary IMA object mask with regions created around objects segmented as PSD regions using IMA. The filtered PSDs are marked in green while the region boundaries are shown in yellow. (B and D) The IMA and thresholding parameters employed for filtering PSDs from STED PSD95 image as a source image.

Article Snippet: Object-based segmentation of synaptic puncta using IMA in MetaMorph software (A) A source image as confocal PSD95 image selected for specific objects based on length, breadth, and area filters. (B) A display of filtering parameters in IMA. (C) Object data for the synaptic puncta obtained through IMA. (D) A binary IMA object mask created as an output image. (E and F) Dynamic data exchange command for exporting the object data on postsynaptic puncta to an excel file. g. Create ROIs on the filtered objects (refer above to step f).

Techniques: Functional Assay, Software

Kaplan-Meier curve showing gestational age at birth with DNA methylation levels of cg11408933 ( PCDH1 , protocadherin 1) dichotomized at the median. Group 1 of the CpG cg11408933 includes subjects with lower DNAm levels and group 2 subjects with higher DNAm levels.

Journal: Epigenetics Insights

Article Title: Paternal DNA Methylation May Be Associated With Gestational Age at Birth

doi: 10.1177/2516865720930701

Figure Lengend Snippet: Kaplan-Meier curve showing gestational age at birth with DNA methylation levels of cg11408933 ( PCDH1 , protocadherin 1) dichotomized at the median. Group 1 of the CpG cg11408933 includes subjects with lower DNAm levels and group 2 subjects with higher DNAm levels.

Article Snippet: The Bioconductor IMA (Illumina methylation analyzer) package and the ComBat package were applied to preprocess raw DNAm data, including removing background noise, adjusting for inter-array variation, performing peak correction, and removing batch effects.

Techniques: DNA Methylation Assay