Image Editing Techniques for Sample Analyses

Description:

­Immunohistochemical staining (IHC) and immunofluorescence (IF) staining of paraffin embedded tissue samples are routinely practiced to observe protein expression in both laboratory settings and for diagnoses. Current techniques used to quantify them are slow and unreliable rendering the staining procedures time consuming and variable in sensitivity, specificity, and reproducibility. Often manual operations such as clicking on individual cells or opening individual files one by one are required by the user, further slowing the process.
 
Kristin Huber at Arizona State University has developed a java-based technology/software application that can rapidly edit and analyze tissue samples. This app has a user-friendly interface, is less time-consuming and provides reliable results compared to conventional techniques. All images in a folder (stained within a single stain type) can be efficiently analyzed after a user selects the desired settings on the first image. In contrast to other programs which use the number of clicks for counting cells, this software can provide ‘cell count’ of similarly stained cells by virtually clearing cells stained differently.
 
This application has the potential to significantly cut down on analysis times in tissue imaging while providing consistent results and increased functionality.
 
Potential Applications
  • App for image editing and analyses
    • Diagnoses
    • Tissue engineering
    • Biomaterials
    • Microscopic image analysis in biology, medicine and biomedical sciences
    • Research
Benefits and Advantages
  • Easier to use and gives more consistent results compared to competitive products
  • Requires significantly less time to analyze the samples
  • Images can be analyzed individually or an entire folder of images can be clicked through and analyzed
  • Can analyze images stained for analysis of structure, signal or colocalization of stain
  • Can process different functions of ‘cell count’ and ‘percent signal’ for single stained as well as multiple stained specimens
  • Can count cells of a desired color or colors by clearing cells that fall outside the selected margin of error in RGB value
  • Additional features can be easily and efficiently added to this software by other developers
  • Enables manipulation RGB (red, green and blue) HSB (hue, saturation and brightness) and other pixel information collected from images
For more information about this opportunity, please see
Case ID:
M21-165L
Published:
02-01-2022
Last Updated:
04-19-2022

Inventor(s):

Kristin Huber

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