The main process is now complete.
[master-thesis.git] / Parasitemia / Parasitemia / ParasitesMarker.fs
1 module ParasitesMarker
2
3 open System.Drawing
4
5 open Emgu.CV
6 open Emgu.CV.Structure
7
8 type Result = {
9 darkStain: Image<Gray, byte>
10 stain: Image<Gray, byte>
11 infection: Image<Gray, byte> }
12
13 // Create three binary markers :
14 // * 'Dark stain' corresponds to the colored pixel, it's independent of the size of the areas.
15 // * 'Stain' corresponds to the stain around the parasites.
16 // * 'Infection' corresponds to the parasite. It shouldn't contain thrombocytes.
17 let find (green: Image<Gray, float32>) (filteredGreen: Image<Gray, float32>) (kmediansResult: KMedians.Result) (config: Config.Config) : Result =
18
19 let green = ImgTools.gaussianFilter green 1.0
20
21 // We use the filtered image to find the dark stain.
22 let { KMedians.fg = fg; KMedians.median_bg = median_bg; KMedians.median_fg = median_fg; KMedians.d_fg = d_fg } = kmediansResult
23 let darkStain = d_fg.Cmp(median_bg * config.darkStainLevel, CvEnum.CmpType.GreaterThan)
24 darkStain._And(filteredGreen.Cmp(median_fg, CvEnum.CmpType.LessThan))
25 darkStain._And(fg)
26
27 let fgFloat = (fg / 255.0).Convert<Gray, float32>()
28 let greenWithoutBg = green.Copy()
29 greenWithoutBg.SetValue(Gray(0.0), fg.Not())
30
31 let findSmears (sigma: float) (level: float) : Image<Gray, byte> =
32 let greenWithoutBgSmoothed = ImgTools.gaussianFilter greenWithoutBg sigma
33 let fgSmoothed = ImgTools.gaussianFilter fgFloat sigma
34
35 let smears = (greenWithoutBg.Mul(fgSmoothed)).Cmp(greenWithoutBgSmoothed.Mul(level), CvEnum.CmpType.LessThan)
36 smears._And(fg)
37 smears
38
39 { darkStain = darkStain;
40 stain = findSmears config.stainSigma config.stainLevel
41 infection = findSmears config.infectionSigma config.infectionLevel }
42
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