module Classifier open System open System.Collections.Generic open System.Drawing open Emgu.CV open Emgu.CV.Structure open Types open Utils type private EllipseFlaggedKd (e: Ellipse) = inherit Ellipse (e.Cx, e.Cy, e.A, e.B, e.Alpha) member val Removed = false with get, set interface KdTree.I2DCoords with member this.X = this.Cx member this.Y = this.Cy let findCells (ellipses: Ellipse list) (parasites: ParasitesMarker.Result) (img: Image) (config: Config.Config) : Cell list = if ellipses.IsEmpty then [] else 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) } // The minimum window to contain a given ellipse. let ellipseWindow (e: Ellipse) = let cx, cy = roundInt e.Cx, roundInt e.Cy let a = int (e.A + 0.5f) cx - a, cy - a, cx + a, cy + a let w = img.Width let w_f = float32 w let h = img.Height let h_f = float32 h // Return 'true' if the point 'p' is owned by e. // The lines represents all intersections with other ellipses. let pixelOwnedByE (p: PointD) (e: Ellipse) (others: (Ellipse * Line) list) = e.Contains p.X p.Y && seq { let c = PointD(e.Cx, e.Cy) for e', d1 in others do let d2 = Utils.lineFromTwoPoints c p let c' = PointD(e'.Cx, e'.Cy) let v = pointFromTwoLines d1 (lineFromTwoPoints c c') let case1 = sign (v.X - c.X) <> sign (v.X - c'.X) || Utils.squaredDistanceTwoPoints v c > Utils.squaredDistanceTwoPoints v c' if d2.Valid then let p' = Utils.pointFromTwoLines d1 d2 // Yield 'false' when the point is owned by another ellipse. if case1 then yield sign (c.X - p.X) <> sign (c.X - p'.X) || Utils.squaredDistanceTwoPoints c p' > Utils.squaredDistanceTwoPoints c p else yield sign (c.X - p.X) = sign (c.X - p'.X) && Utils.squaredDistanceTwoPoints c p' < Utils.squaredDistanceTwoPoints c p else yield case1 } |> Seq.forall id let ellipses = ellipses |> List.map EllipseFlaggedKd // 1) Associate touching ellipses with each ellipses and remove ellipse with more than two intersections. let tree = KdTree.Tree.BuildTree ellipses let neighbors (e: EllipseFlaggedKd) : (EllipseFlaggedKd * PointD * PointD) list = if not e.Removed then tree.Search (searchRegion e) // We only keep the ellipses touching 'e'. |> List.choose (fun otherE -> if e <> otherE then match EEOver.EEOverlapArea e otherE with | Some (_, px, _) when px.Length > 2 -> otherE.Removed <- true None | Some (area, px, py) when area > 0.f && px.Length = 2 -> Some (otherE, PointD(px.[0], py.[0]), PointD(px.[1], py.[1])) | _ -> None else None ) else [] // 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 // 3) Remove ellipses with a high standard deviation (high contrast). let imgData = img.Data let globalStdDeviation = MathNet.Numerics.Statistics.Statistics.PopulationStandardDeviation(seq { for y in 0 .. h - 1 do for x in 0 .. w - 1 do yield float imgData.[y, x, 0] }) 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 = 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] }) 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 for e, neighbors in ellipsesWithNeigbors do if not e.Removed then let minX, minY, maxX, maxY = ellipseWindow e let mutable area = 0 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 let p = PointD(float32 x, float32 y) if pixelOwnedByE p e (neighbors |> List.choose (fun (otherE, p1, p2) -> if otherE.Removed then None else Some (otherE :> Ellipse, Utils.lineFromTwoPoints p1 p2))) then area <- area + 1 if area < int minArea then e.Removed <- true // 5) Define pixels associated to each ellipse and create the cells. ellipsesWithNeigbors |> List.choose (fun (e, neighbors) -> if e.Removed then None else let minX, minY, maxX, maxY = ellipseWindow e let infectedPixels = List() let mutable stainPixels = 0 let mutable darkStainPixels = 0 let mutable nbElement = 0 let elements = new Matrix(maxY - minY + 1, maxX - minX + 1) for y in minY .. maxY do for x in minX .. maxX do let p = PointD(float32 x, float32 y) if pixelOwnedByE p e (neighbors |> List.choose (fun (otherE, p1, p2) -> if otherE.Removed then None else Some (otherE :> Ellipse, Utils.lineFromTwoPoints p1 p2))) then elements.[y-minY, x-minX] <- 1uy nbElement <- nbElement + 1 if infection.Data.[y, x, 0] > 0uy then infectedPixels.Add(Point(x, y)) if parasites.stain.Data.[y, x, 0] > 0uy then stainPixels <- stainPixels + 1 if parasites.darkStain.Data.[y, x, 0] > 0uy then darkStainPixels <- darkStainPixels + 1 let cellClass = if float darkStainPixels > config.Parameters.maxDarkStainRatio * (float nbElement) || float stainPixels > config.Parameters.maxStainRatio * (float nbElement) then Peculiar elif infectedPixels.Count >= 1 then let infectionToRemove = ImgTools.connectedComponents parasites.stain infectedPixels for p in infectionToRemove do infection.Data.[p.Y, p.X, 0] <- 0uy InfectedRBC else HealthyRBC Some { cellClass = cellClass center = Point(roundInt e.Cx, roundInt e.Cy) stainArea = stainPixels elements = elements })