GitHub - epaxon/ImageComponentParser: Matlab GUI for Automated Voltage and Calcium Imaging Analysis

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Matlab GUI for Automated Voltage and Calcium Imaging Analysis

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Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
FastICA_25		FastICA_25
GUILayout-v1p13		GUILayout-v1p13
Resources		Resources
doc		doc
ecc		ecc
.gitattributes		.gitattributes
.gitignore		.gitignore
AxesEventNotifier.m		AxesEventNotifier.m
DataEvent.m		DataEvent.m
DoubleScroll.m		DoubleScroll.m
FigureEventNotifier.m		FigureEventNotifier.m
ImageComponentParser.asv		ImageComponentParser.asv
ImageComponentParser.m		ImageComponentParser.m
README.txt		README.txt
RoiEditor.m		RoiEditor.m
VDoubleScroll.m		VDoubleScroll.m
align_im_stack.m		align_im_stack.m
calc_rois_from_components.m		calc_rois_from_components.m
gpl.txt		gpl.txt
icp_basics.m		icp_basics.m
install_icp.m		install_icp.m
make_feature_matrix.m		make_feature_matrix.m
max_corr_thresh.m		max_corr_thresh.m
max_corr_thresh_all.m		max_corr_thresh_all.m
mean_roi.m		mean_roi.m
norm_range.m		norm_range.m
oval2xy.m		oval2xy.m
oval_image.m		oval_image.m
plot_oval.m		plot_oval.m
sample_data.mat		sample_data.mat
segment_ics.m		segment_ics.m
tifread.m		tifread.m
viz_function.m		viz_function.m
xyrra_image.m		xyrra_image.m

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Image Component Parser is a Matlab GUI for automated analysis of Voltage and Calcium imaging data.

The primary function of ICP is to decompose imaging data into independent components using PCA and ICA. This procedure consists of 4 stages:
1. Preprocessing on the Data - blur, down sample, filter
2. Principle Components Analysis
3. Indpendent Compnents Analysis
4. Post processing - segmentation, ROI generation, and clustering.