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Counting cells in a blood smear using convolution as the pattern matching strategy

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Cells counting

Counting red blood cells in blood smear.

Goal of the project

The goal of this project is to count the number of blood cells in a 2D image of a blood smear.

Steps

I use several steps of image pre-processing to obtain a binary image from which it is easy to count the cells by counting the white zones in the image.

Most effective method

The most accurate method I found is a pattern matching approach.

  1. I take a reference cell, and compute its convolution against the complete image. Higher intensity zones corresponds to cells center.

  2. Then, I apply a threshold at a given percentage of the histogram to get a binary image where the cells are white circles and the rest is black.

  3. Finally, I count the white zones in the binary image.

Notes

This project was part of my Master Of Science curriculum at Centrale Nantes.

This project is no longer updated.