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Iba1+ cells in the PEC are generally sparsely distributed around the posterior eye cup, but manual quantification of these cells is time consuming. Therefore we developed a second semi-automated MatLab code to quantify single Iba1+ cells. The operator is presented with masked, randomized images and allowed to remove non-specific fluorescence (fa…

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Novartis/Cell-Quant

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Cell_quant_ADRIAN_V2

License

Copyright 2018 Novartis Institutes for BioMedidical Research Inc. Licensed under the Apache License, Version 2.0 (the "License"); ou may not use this file except in complicane with the License. You may obtain a copy of the License at http://www.apache.org/licenses/License-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distrubuted on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONITIONS OF ANY KIND, either express or implied. See the License for the specific Language Governing the permissions and limiations under the License.

Overview

This MatLab Image Analysis code will quantify the number of postive ojects in an image using size and intensity thresholds.

This analysis requires the Image Processing Toolbox and Signal Processing Toolbox for MatLab to function.

All files must be Tagged Image Format (.tiff). Images will be displayed to the user in a masked, and randomized fashion to avoid an biases.

Procedure

  1. Run the script in MatLab
  2. Direct the program to the folder containing the images
  3. Crop out any non-specific staining, or unwanted signal
  4. Press the "space bar" to advance
  5. Click to add any cells back to the image analysis
  6. Press the "space bar" to advance
  7. Once all images have been analyzed an excel file will compile the results

Tips

A temporary data file will be created at the start of the analysis to keep track of any work in case MatLab shuts down accidentally. This file can be found in the same folder as the code. Delete this file to run a new analysis.

Line 35 dinfes the backgroun that will be subtracted from the original image. The radius of the of the structured element disk is defined at the end of the line. Increasing the radius of the disk decreases how much background is removed, whereas decreasing the radius of the disk will increase how much background is removed.

Line 40 is the intensity mask, any objects below the designated threshold will be removed from the analysis. Adjusting the value of the numerator will change the threshold. Only numbers between 0 and 255 can be used.

Line 41 is the large size exclusion, this will remove objects larger than the designated pixel area. Adjusting this value will change the exclusion/inclusion criteria of larger opbjects.

Line 42 is the small size exlusion, this will remove objects smaller than the designated pixel area. Adjusting this value will change the exclusion/ inclusion criteria of smaller objects.

About

Iba1+ cells in the PEC are generally sparsely distributed around the posterior eye cup, but manual quantification of these cells is time consuming. Therefore we developed a second semi-automated MatLab code to quantify single Iba1+ cells. The operator is presented with masked, randomized images and allowed to remove non-specific fluorescence (fa…

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