Hello Lorenzo, Try to locate related R packages from here:
http://cran.r-project.org/web/views/MedicalImaging.html

On 14 October 2013 22:23, Lorenzo Isella <lorenzo.ise...@gmail.com> wrote:
> 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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