X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FClassifier.fs;h=121a7f53d3bbfaddebee7ba2265602c9950d12e7;hp=1a2212991ec0b954d947d8b8ea1b41d4a5b9dc74;hb=05be8164d308447b916544ae3ce4211500dfd8da;hpb=ee562c3b613791fd89a5c322546229e9d364cafb diff --git a/Parasitemia/Parasitemia/Classifier.fs b/Parasitemia/Parasitemia/Classifier.fs index 1a22129..121a7f5 100644 --- a/Parasitemia/Parasitemia/Classifier.fs +++ b/Parasitemia/Parasitemia/Classifier.fs @@ -29,10 +29,10 @@ let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img: let infection = parasites.infection.Copy() // To avoid to modify the parameter. // This is the minimum window size to check if other ellipses touch 'e'. - let searchRegion (e: Ellipse) = { KdTree.minX = e.Cx - (e.A + config.RBCMaxRadius) - KdTree.maxX = e.Cx + (e.A + config.RBCMaxRadius) - KdTree.minY = e.Cy - (e.A + config.RBCMaxRadius) - KdTree.maxY = e.Cy + (e.A + config.RBCMaxRadius) } + let searchRegion (e: Ellipse) = { KdTree.minX = e.Cx - (e.A + config.RBCRadius.Max) + KdTree.maxX = e.Cx + (e.A + config.RBCRadius.Max) + KdTree.minY = e.Cy - (e.A + config.RBCRadius.Max) + KdTree.maxY = e.Cy + (e.A + config.RBCRadius.Max) } // The minimum window to contain a given ellipse. let ellipseWindow (e: Ellipse) = @@ -97,7 +97,6 @@ let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img: // We reverse the list to get the lower score ellipses first. let ellipsesWithNeigbors = ellipses |> List.map (fun e -> e, neighbors e) |> List.rev - // 2) Remove ellipses touching the edges. for e in ellipses do if e.isOutside w_f h_f then e.Removed <- true @@ -125,42 +124,9 @@ let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img: if stdDeviation > globalStdDeviation * config.Parameters.standardDeviationMaxRatio then e.Removed <- true -(* - let imgData = img.Data - let stdDeviations = [ - for e in ellipses do - if not e.Removed - then - let shrinkedE = e.Scale 0.9f - let minX, minY, maxX, maxY = ellipseWindow shrinkedE - - let stdDeviation = float32 <| MathNet.Numerics.Statistics.Statistics.StandardDeviation (seq { - for y in (if minY < 0 then 0 else minY) .. (if maxY >= h then h - 1 else maxY) do - for x in (if minX < 0 then 0 else minX) .. (if maxX >= w then w - 1 else maxX) do - if shrinkedE.Contains (float32 x) (float32 y) - then - yield float imgData.[y, x, 0] }) - - e.StdDeviation <- stdDeviation - yield stdDeviation ] - - // We use Otsu and eliminate some cells only if the curve may be bimodal. - // See https://en.wikipedia.org/wiki/Multimodal_distribution#Bimodality_coefficient - let skewness, kurtosis = MathNet.Numerics.Statistics.Statistics.PopulationSkewnessKurtosis (stdDeviations |> List.map float) - let n = float stdDeviations.Length - let bimodalityCoefficient = (skewness ** 2. + 1.) / (kurtosis + 3. * (n - 1.) ** 2. / ((n - 2.) * (n - 3.))) - - if bimodalityCoefficient > 5. / 9. - then - let hist = ImgTools.histogram stdDeviations 200 - let thresh, _, _ = ImgTools.otsu hist - for e in ellipses do - if not e.Removed && e.StdDeviation > thresh - then e.Removed <- true -*) // 4) Remove ellipses with little area. - let minArea = config.RBCMinArea + let minArea = config.RBCRadius.MinArea for e, neighbors in ellipsesWithNeigbors do if not e.Removed then