static void Main(string[] args)
{
#region init
if (0 == args.Length)
{
Console.WriteLine("no slide name");
return;
}
var slideName = args[0];
var processinHelper = new Processing(slideName);
var slide = processinHelper.Slide;
#endregion init
var part = new WsiPartitioner(new Rectangle(new Point(0, 0), slide.Size), new Size(1000, 1000), new Size(0, 0), 1.0);
var tissueData = new TiledProcessInformation<bool>(part, slideName);
#region global tissue detection
int overviewImageWidth = slide.Size.Width / OverviewTileSize;
int overviewImageHeight = slide.Size.Height / OverviewTileSize;
Bitmap overviewImage = slide.GetImagePart(0, 0, slide.Size.Width, slide.Size.Height, overviewImageWidth, overviewImageHeight);
var bitmapProcessor = new BitmapProcessor(overviewImage);
ObjectLayer overviewLayer = new TissueDetector().Execute(bitmapProcessor, Radius, NoiseLevel);
bitmapProcessor.Dispose();
DrawObjectsToImage(overviewImage, overviewLayer, Color.Black);
overviewImage.Save(processinHelper.DataPath + "tissueDetectionOverview.png");
#endregion global tissue detection
//part.Tiles[]
foreach (var tile in part)
{
#region global tissue detection
var rect = tile.SourceRect;
int overviewX = rect.X / OverviewTileSize;
int overviewY = rect.Y / OverviewTileSize;
int windowSize = rect.Width / OverviewTileSize;
bool tileInObject = true;
int partsOutside = 0;
for (int y = 0; y < windowSize; y++)
{
for (int x = 0; x < windowSize; x++)
{
int newX = overviewX + x;
int newY = overviewY + y;
if (newX < 0 || newX >= overviewLayer.Map.Width || newY < 0 || newY >= overviewLayer.Map.Height) { continue; }
uint id = overviewLayer.Map[newX, newY];
if (id != 0) continue;
partsOutside++;
if (!(partsOutside >= Math.Pow(windowSize + 1, 2) * 0.75)) continue;
tileInObject = false;
break;
}
if (!tileInObject) { break; }
}
tissueData.AddDataToCurrentTile(tileInObject);
#endregion global tissue detection
if (tileInObject) Console.WriteLine(tile.SourceRect + ":" + partsOutside);
}
tissueData.ToFile(processinHelper.DataPath + "tissueData.tpi");
using (Bitmap b = tissueData.GenerateHeatMap(tissue => tissue ? Color.Green : Color.Red))
b.Save(processinHelper.DataPath + "tissueData.png");
Console.WriteLine("done");
Console.ReadKey();
}
private static void processInput()
{
int Radius = 2;
int NoiseLevel = 10;
Console.WriteLine("Processing Input...");
foreach (var import in importItems)
{
Console.WriteLine();
Console.WriteLine(import.FileName);
Console.WriteLine("Slide extrahieren...");
var processingHelper = new Processing(import.FileName);
var slide = processingHelper.Slide;
Console.WriteLine("Ausschnitt aus Slide extrahieren mit originaler Auflösung...");
int partImageWidth = import.LowerRight.X - import.UpperLeft.X;
int partImageHeight = import.LowerRight.Y - import.UpperLeft.Y;
Bitmap partImage = slide.GetImagePart(
import.UpperLeft.X, import.UpperLeft.Y,
partImageWidth, partImageHeight,
partImageWidth, partImageHeight
);
#region global tissue detection
Console.WriteLine("Gewebe suchen und in separatem Layer speichern...");
var bitmapProcessor = new BitmapProcessor(partImage);
ObjectLayer overviewLayer = new TissueDetector().Execute(bitmapProcessor, Radius, NoiseLevel);
bitmapProcessor.Dispose();
Console.WriteLine("Gewebe-Layer in Ausschnitt zeichnen + speichern...");
DrawObjectsToImage(partImage, overviewLayer, Color.Black);
partImage.Save(processingHelper.DataPath + "ImagePartTissue.png");
#endregion global tissue detection
#region Deconvolution
Console.WriteLine("Execute deconvolution 3...");
var gpX = new ColorDeconvolution().Get3rdStain(partImage, ColorDeconvolution.KnownStain.HaematoxylinEosin);
gpX.Dispose();
Bitmap gpX_bmp = gpX.Bitmap;
gpX_bmp.Save(processingHelper.DataPath + "ImagePartColor3.png");
Console.WriteLine("Execute deconvolution 2...");
var gpE = new ColorDeconvolution().Get2ndStain(partImage, ColorDeconvolution.KnownStain.HaematoxylinEosin);
gpE.Dispose();
Bitmap gpE_bmp = gpE.Bitmap;
gpE_bmp.Save(processingHelper.DataPath + "ImagePartColor2.png");
Console.WriteLine("Execute deconvolution 1...");
var gpH = new ColorDeconvolution().Get1stStain(partImage, ColorDeconvolution.KnownStain.HaematoxylinEosin);
gpH.Dispose();
Bitmap gpH_bmp = gpH.Bitmap;
gpH_bmp.Save(processingHelper.DataPath + "ImagePartColor1.png");
#endregion Deconvolution
#region execute edge detection
Console.WriteLine("Execute edge detection...");
SobelResponse responseH = Filtering.ExecuteSobel(gpH_bmp);
SobelResponse responseE = Filtering.ExecuteSobel(gpE_bmp);
var substracted = new double[responseH.Size.Width, responseH.Size.Height];
var substractedRange = new Range<double>();
for (var x = 0; x < responseH.Size.Width; x++)
{
for (var y = 0; y < responseH.Size.Height; y++)
{
var value = Math.Max(0, responseE.Gradient[x, y] - responseH.Gradient[x, y]);
substracted[x, y] = value;
substractedRange.Add(value);
}
}
double[,] nonMaximumSupression = Filtering.ExecuteNonMaximumSupression(substracted, responseE.Orientation);
Bitmap edges = Visualization.Visualize(nonMaximumSupression, Visualization.CreateColorizing(substractedRange.Maximum));
edges.Save(processingHelper.DataPath + "ImagePartEdges.png");
#endregion execute edge detection
exportItems.Add(
new Ausgabe {
Identify = import.Identify,
Result = false,
Message = "kein Fehler"
}
);
}
}
