Saturday, April 9, 2016

Image segmentation, part 1

I often want to calculate numbers that quantify features in images. For example, the picture below is a cross-section of a piece of heart muscle. The edges are mostly white/gray and are the background of the slide. The light orange parts are muscle. The red parts are collagen.

I want to calculate the relative content of collagen, that is the number of pixels that are collagen divided by the number of pixels that aren't background.

When my lab has done this in the past, we've segmented the image by thresholding in the RGB plane. The screenshot below shows an initial attempt using the Color Thresholding tool in Fiji.

I think this approach works, eventually, but it requires a lot of fiddling to get the thresholds right, and it's definitely subjective. When I came across this page in the MATLAB documentation, I wondered if k-means clustering might be a better option.

We'll describe that approach in the next post.

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