private static void Main(string[] args)
{
foreach (var slideName in Util.GetSlideFilenames(args))
{
using (var slideCache = new SlideCache(slideName)){
var hValues = File.Exists(slideCache.DataPath + "hValues.xml")?SlidePartitioner <double> .Load(slideCache.DataPath + "hValues.xml"):new SlidePartitioner <double>(slideCache.Slide, 1f, new Size(2000, 2000));
var eValues = File.Exists(slideCache.DataPath + "eValues.xml")?SlidePartitioner <double> .Load(slideCache.DataPath + "eValues.xml"):hValues.Duplicate <double>();
var hRange = new Range <double>();
var eRange = new Range <double>();
foreach (var tile in hValues.Values)
{
using (Bitmap tileImage = slideCache.Slide.GetImagePart(tile), hImage = tileImage.Clone() as Bitmap, eImage = tileImage.Clone() as Bitmap){
var gpH = new ColorDeconvolution().Get1stStain(hImage, ColorDeconvolution.KnownStain.HaematoxylinEosin);
var gpE = new ColorDeconvolution().Get2ndStain(eImage, ColorDeconvolution.KnownStain.HaematoxylinEosin);
var hSum = 0u;
var eSum = 0u;
var cnt = 0;
foreach (var grayscalePixel in gpH.Pixels())
{
hSum += grayscalePixel.V;
eSum += gpE.GetPixel(grayscalePixel.X, grayscalePixel.Y);
cnt++;
}
var meanH = (double)hSum / (double)cnt;
tile.Data = meanH;
hRange.Add(meanH);
var meanE = (double)eSum / (double)cnt;
eValues[tile.Index].Data = meanE;
eRange.Add(meanE);
gpH.Dispose();
gpE.Dispose();
if (slideCache.Slide.GetAnnotationsInArea(tile.SourceArea).Any())
{
var tileCache = slideCache.GetTileCache(tile.Index);
tileCache.SetImage("rgb", tileImage);
tileCache.SetImage("h", gpH.Bitmap);
tileCache.SetImage("e", gpE.Bitmap);
}
}
Console.WriteLine(slideCache.SlideName + "-" + tile.Index + " done");
}
var range = new Range <double> {
hRange.Minimum, hRange.Maximum, eRange.Minimum, eRange.Maximum
};
Func <double, Color> toColor = v => {
var c = (int)Math.Round(range.Normalize(v) * 255d);
return(Color.FromArgb(c, c, c));
};
slideCache.SetImage("hValues", hValues.GenerateHeatMap(toColor));
slideCache.SetImage("eValues", eValues.GenerateHeatMap(toColor));
slideCache.SetImage("overview", slideCache.Slide.GetImagePart(0, 0, slideCache.Slide.Size.Width, slideCache.Slide.Size.Height, hValues.Columns, hValues.Rows));
hValues.Save(slideCache.DataPath + "hValues.xml");
eValues.Save(slideCache.DataPath + "eValues.xml");
}
}
}
public static TissueAnnotationClass ComputeFeatures(TissueAnnotationClass tissueAnnotationOld, Bitmap image)
{
using (Bitmap hImage = image.Clone() as Bitmap, eImage = image.Clone() as Bitmap)
{
TissueAnnotationClass tissueAnnotation = tissueAnnotationOld.Clone();
int imageSize = 0;
//H und E Werte aus Bild ermitteln
var gpH = new ColorDeconvolution().Get1stStain(hImage, ColorDeconvolution.KnownStain.HaematoxylinEosin);
var gpE = new ColorDeconvolution().Get2ndStain(eImage, ColorDeconvolution.KnownStain.HaematoxylinEosin);
uint[] hHistogram = new uint[256];
uint[] eHistogram = new uint[256];
foreach (var grayscalePixel in gpH.Pixels())
{
imageSize++;
hHistogram[grayscalePixel.V]++;
eHistogram[gpE.GetPixel(grayscalePixel.X, grayscalePixel.Y)]++;
}
//Segmentation aus dem Bild ermitteln
//Layers erstellen
var luminaLayer = ObjectLayerCreate.CreateLuminaLayer(image);
var coresLayer = ObjectLayerCreate.CreateCoresLayer(image);
//Features dem layer hinzufügen
coresLayer =
ObjectLayerrUtils.AddFeatureFormFactor(
ObjectLayerrUtils.AddFeatureCenterPoint(coresLayer));
luminaLayer =
ObjectLayerrUtils.AddFeatureCoresInNear(
ObjectLayerrUtils.AddFeatureFormFactor(luminaLayer), coresLayer);
//Alle Features ermitteln und in Listen schreiben --> sortiert um anschließend Mid und Avverage auszurechen
List <uint> hHistogramList = histogramToList(hHistogram);
List <uint> eHistogramList = histogramToList(eHistogram);
List <uint> coresSizeList = ObjectLayerrUtils.GetFeatureValueList(coresLayer, "area");
List <uint> luminaSizeList = ObjectLayerrUtils.GetFeatureValueList(luminaLayer, "area");
List <uint> coresFormFactorList = ObjectLayerrUtils.GetFeatureValueList(coresLayer,
"FormFactorOfContour");
List <uint> luminaFormFactorWithSize = new List <uint>();
List <uint> luminaCoresInNear = new List <uint>();
List <uint> luminaCoresInNearWithForm = new List <uint>();
foreach (var imageObject in luminaLayer.Objects)
{
var coresInNear = imageObject.Features.GetFeatureByName("coresInNear").Value;
var formFactor = imageObject.Features.GetFeatureByName("FormFactorOfContour").Value;
var area = imageObject.Features.GetFeatureByName("area").Value;
if (Math.Abs(coresInNear) != 0)
{
luminaCoresInNear.Add((uint)(area / coresInNear));
luminaCoresInNearWithForm.Add((uint)((area * formFactor) / coresInNear));
}
if (Math.Abs(formFactor) != 0)
{
luminaFormFactorWithSize.Add((uint)(area / (2 * formFactor)));
}
}
luminaCoresInNear.Sort();
luminaCoresInNearWithForm.Sort();
luminaFormFactorWithSize.Sort();
//alle Features dem Object hinzufügen
tissueAnnotation.Q25H = calcQuantil(hHistogramList, 0.25);
tissueAnnotation.MeanH = calcQuantil(hHistogramList, 0.5);
tissueAnnotation.Q75H = calcQuantil(hHistogramList, 0.75);
tissueAnnotation.Q25E = calcQuantil(eHistogramList, 0.25);
tissueAnnotation.MeanE = calcQuantil(eHistogramList, 0.5);
tissueAnnotation.Q75E = calcQuantil(eHistogramList, 0.75);
if (coresSizeList.Count == 0)
{
tissueAnnotation.CountCores = 0u;
}
else
{
tissueAnnotation.CountCores = (uint)(imageSize / coresSizeList.Count);
}
if (luminaSizeList.Count == 0)
{
tissueAnnotation.CountLumina = 0u;
}
else
{
tissueAnnotation.CountLumina = (uint)(imageSize / luminaSizeList.Count);
}
tissueAnnotation.MidCoresSize = calcMid(coresSizeList);
tissueAnnotation.MeanCoresSize = calcQuantil(coresSizeList, 0.5);
tissueAnnotation.Q25CoresSize = calcQuantil(coresSizeList, 0.25);
tissueAnnotation.Q75CoresSize = calcQuantil(coresSizeList, 0.75);
tissueAnnotation.MidLuminaSize = calcMid(luminaSizeList);
tissueAnnotation.MeanLuminaSize = calcQuantil(luminaSizeList, 0.5);
tissueAnnotation.Q25LuminaSize = calcQuantil(luminaSizeList, 0.25);
tissueAnnotation.Q75LuminaSize = calcQuantil(luminaSizeList, 0.75);
if (coresSizeList.Count == 0)
{
tissueAnnotation.DensityCores = 0;
}
else
{
tissueAnnotation.DensityCores = (uint)(imageSize /
coresSizeList.Count);
}
tissueAnnotation.MidFormFactorCores = calcMid(coresFormFactorList);
tissueAnnotation.MeanFormFactorCores = calcQuantil(coresFormFactorList, 0.5);
tissueAnnotation.Q25FormFactorCores = calcQuantil(coresFormFactorList, 0.25);
tissueAnnotation.Q75FormFactorCores = calcQuantil(coresFormFactorList, 0.75);
tissueAnnotation.MidFormFactorLuminaWithSize = calcMid(luminaFormFactorWithSize);
tissueAnnotation.MeanFormFactorLuminaWithSize = calcQuantil(luminaFormFactorWithSize, 0.5);
tissueAnnotation.Q25FormFactorLuminaWithSize = calcQuantil(luminaFormFactorWithSize, 0.25);
tissueAnnotation.Q75FormFactorLuminaWithSize = calcQuantil(luminaFormFactorWithSize, 0.75);
tissueAnnotation.MidDensityLuminaCoresInNear = calcMid(luminaCoresInNear);
tissueAnnotation.MeanDensityLuminaCoresInNear = calcQuantil(luminaCoresInNear, 0.5);
tissueAnnotation.Q25DensityLuminaCoresInNear = calcQuantil(luminaCoresInNear, 0.25);
tissueAnnotation.Q75DensityLuminaCoresInNear = calcQuantil(luminaCoresInNear, 0.75);
tissueAnnotation.MidDensityFormFactorLuminaCoresInNear = calcMid(luminaCoresInNearWithForm);
tissueAnnotation.MeanDensityFormFactorLuminaCoresInNear =
calcQuantil(luminaCoresInNearWithForm, 0.5);
tissueAnnotation.Q25DensityFormFactorLuminaCoresInNear =
calcQuantil(luminaCoresInNearWithForm, 0.25);
tissueAnnotation.Q75DensityFormFactorLuminaCoresInNear =
calcQuantil(luminaCoresInNearWithForm, 0.75);
return(tissueAnnotation);
}
}
