Dear All,
For a project I am given a set of images. They represent either healthy or
tumoral tissue, but the specific nature of the images does not matter.
I need to train a classifier which is expected to tell me in which
category (let's call it 0 vs 1) each image falls.
I am thinking about a random forest classifier, but I am uncertain about a
couple of (fairly important) points
(1) The size of the images varies, so for instance the number of pixels is
not the same for every image and as a consequence some methodologies (e.g.
the PCA) when applied to these images will lead to results not immediately
comparable. Is trying to blur/flatten the images a good idea to have
always (artificially) the same size (number of pixels) for every image?
(2) Which features do you recommend to associate\calculate for every
image? This is what I will use to train my model upon.
Any suggestion is welcome.
Cheers
Lorenzo
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