Document Type
Data
Publication Title
Comparing Performance of Spectral Image Analysis Approaches for Detection of Cellular Signals in Time-Lapse Hyperspectral Imaging Fluorescence Excitation-Scanning Microscopy
Department
Chemical and Biomolecular Engineering
Description/Summary of Research
The dataset contains raw and processed hyperspectral timelapse image data that are described in the manuscript:
Parker, M., Annamdevula, N. S., Pleshinger, D., Ijaz, Z., Jalkh, J., Penn, R., Deshpande, D., Rich, T. C. & Leavesley, S. J. Comparing Performance of Spectral Image Analysis Approaches for Detection of Cellular Signals in Time-Lapse Hyperspectral Imaging Fluorescence Excitation-Scanning Microscopy. Bioengineering 10, 642 (2023).
Date of collection
2023
File Format
Zip file with subfolders for each figure
Funders
National Science Foundation (NSF), National Institutes of Health (NIH)
Grant Number
NSF: 1725937; NIH: P01HL066299, R01HL58506, R01HL137030, and R01HL169522
Recommended Citation
Leavesley, Silas J., "Dataset for Manuscript: Comparing Performance of Spectral Image Analysis Approaches for Detection of Cellular Signals in Time-Lapse Hyperspectral Imaging Fluorescence Excitation-Scanning Microscopy" (2023). BioImaging and BioSystems Research. 1.
https://jagworks.southalabama.edu/bioimage_research/1
Included in
Bioimaging and Biomedical Optics Commons, Cellular and Molecular Physiology Commons, Pharmacology Commons
Comments
A detailed author list may be found in the manuscript (see citation).
Hyperspectral imaging datasets are saved as series of tiff files, one for each wavelength. Files may be opened with any of a range of image processing software, such as the opensource ImageJ/FIJI software.