VTK可视化技术之人类颈动脉血管流动 （Visualizing Blood Flow）

Visualizing Blood Flow

该实例中data包含速度向量vector和速率标量scalar。

利用向量可视化技术创建vector glyph。但是由于存在的points太多，因此需要使用滤波器filter选择合适的点的子集。进而创建向量符号。

采用的滤波器为：vtkThresholdPoints  和 vtkMaskPoints

vtkThresholdPoints 滤波器通过定义阈值，选择大于或者小于阈值的点作为子集。

vtkMaskPoints 滤波器通过OnRation 来实例化points进而选择子集。 如果OnRatio=1,则所有数据点都被选择，如果OnRatio=10，则每10个数据点被选择。可以使均匀选择也可以是随机选择。通过RandomModeOn() 和 RandomModeO方法控制。

选择子集之后在子集中采用vtkGlyph3D滤波器，创建圆锥（其方向代表血流方向，大小和颜色反映速度的大小）。

实现代码和效果图如下：

#include 
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int main (int argc, char *argv[])
{
  if (argc < 2)
  {
    std::cout << "Usage: " << argv[0] << " carotid.vtk" << std::endl;
    return EXIT_FAILURE;
  }

  vtkSmartPointer colors =
    vtkSmartPointer::New();

  vtkSmartPointer ren1 =
    vtkSmartPointer::New();

  vtkSmartPointer renWin =
    vtkSmartPointer::New();
  renWin->AddRenderer(ren1);

  vtkSmartPointer iren =
    vtkSmartPointer::New();
  iren->SetRenderWindow(renWin);

// create pipeline
//
  vtkSmartPointer reader =
    vtkSmartPointer::New();
  reader->SetFileName(argv[1]);

  vtkSmartPointer threshold =
    vtkSmartPointer::New();
  threshold->SetInputConnection(reader->GetOutputPort());
  threshold->ThresholdByUpper(200);

  vtkSmartPointer mask =
    vtkSmartPointer::New();
  mask->SetInputConnection(threshold->GetOutputPort());
  mask->SetOnRatio(5);

  vtkSmartPointer cone =
    vtkSmartPointer::New();
  cone->SetResolution(11);
  cone->SetHeight(1);
  cone->SetRadius(0.25);

  vtkSmartPointer cones =
    vtkSmartPointer::New();
  cones->SetInputConnection(mask->GetOutputPort());
  cones->SetSourceConnection(cone->GetOutputPort());
  cones->SetScaleFactor(0.4);
  cones->SetScaleModeToScaleByVector();

  vtkSmartPointer lut =
    vtkSmartPointer::New();
  lut->SetHueRange(.667, 0.0);
  lut->Build();

  double range[2];
  cones->Update();
  range[0] = cones->GetOutput()->GetPointData()->GetScalars()->GetRange()[0];
  range[1] = cones->GetOutput()->GetPointData()->GetScalars()->GetRange()[1];
  std::cout << "range: " << range[0] << ", " << range[1] << std::endl;

  vtkSmartPointer vectorMapper =
    vtkSmartPointer::New();
  vectorMapper->SetInputConnection(cones->GetOutputPort());
  vectorMapper->SetScalarRange(range[0], range[1]);
  vectorMapper->SetLookupTable(lut);

  vtkSmartPointer vectorActor =
    vtkSmartPointer::New();
  vectorActor->SetMapper(vectorMapper);

// contours of speed
  vtkSmartPointer iso =
    vtkSmartPointer::New();
  iso->SetInputConnection(reader->GetOutputPort());
  iso->SetValue(0, 175);

  vtkSmartPointer isoMapper =
    vtkSmartPointer::New();
  isoMapper->SetInputConnection(iso->GetOutputPort());
  isoMapper->ScalarVisibilityOff();

  vtkSmartPointer isoActor =
    vtkSmartPointer::New();
  isoActor->SetMapper(isoMapper);
  isoActor->GetProperty()->SetRepresentationToWireframe();
  isoActor->GetProperty()->SetOpacity(0.25);

// outline
  vtkSmartPointer outline =
    vtkSmartPointer::New();
  outline->SetInputConnection(reader->GetOutputPort());

  vtkSmartPointer outlineMapper =
    vtkSmartPointer::New();
  outlineMapper->SetInputConnection(outline->GetOutputPort());

  vtkSmartPointer outlineActor =
    vtkSmartPointer::New();
  outlineActor->SetMapper(outlineMapper);
  outlineActor->GetProperty()->SetColor(colors->GetColor3d("Black").GetData());

// Add the actors to the renderer, set the background and size
//
  ren1->AddActor(outlineActor);
  ren1->AddActor(vectorActor);
  ren1->AddActor(isoActor);
  ren1->SetBackground(colors->GetColor3d("Wheat").GetData());
  renWin->SetSize(640, 480);

  vtkSmartPointer cam1 =
    vtkSmartPointer::New();
  cam1->SetClippingRange(17.4043, 870.216);
  cam1->SetFocalPoint(136.71, 104.025, 23);
  cam1->SetPosition(204.747, 258.939, 63.7925);
  cam1->SetViewUp(-0.102647, -0.210897, 0.972104);
  cam1->Zoom(1.6);
  ren1->SetActiveCamera(cam1);

// render the image
//
  renWin->Render();
  iren->Start();

  return EXIT_SUCCESS;
}

生成血管速度的streamtubes，可以采用等值面技术。但是streamtubes的起点很那确定。

原因：许多streamers在动脉外边。（数据的测量方法和速度场的分辨率导致），因为数据的分辨率，血液流的边界层不能被捕获，导致在弯道处血液流速的一个分量将 streamtube 指向动脉的外侧。因此很难找到感兴趣结果的streamtube 的起始位置。

解决：源对象 vtkPointSource  和 vtkThresholdPoints

vtkPointSource 生成以指定半径的球体为中心的随机点。只需要找到流管起始点的一个近似位置，然后生成一个随机种子点云。vtkThresholdPoints 用于筛选可能在高流速区域之外生成的点。

主要代码(其余部分与上述代码一样)如下：

// create pipeline
//
  vtkSmartPointer reader =
    vtkSmartPointer::New();
  reader->SetFileName(argv[1]);

  vtkSmartPointer psource =
    vtkSmartPointer::New();
  psource->SetNumberOfPoints(25);
  psource->SetCenter(133.1, 116.3, 5.0);
  psource->SetRadius(2.0);

  vtkSmartPointer threshold =
    vtkSmartPointer::New();
  threshold->SetInputConnection(reader->GetOutputPort());
  threshold->ThresholdByUpper(275);

  vtkSmartPointer streamers =
    vtkSmartPointer::New();
  streamers->SetInputConnection(reader->GetOutputPort());
  streamers->SetSourceConnection(psource->GetOutputPort());
//  streamers->SetMaximumPropagationUnitToTimeUnit();
  streamers->SetMaximumPropagation(100.0);
//  streamers->SetInitialIntegrationStepUnitToCellLengthUnit();
  streamers->SetInitialIntegrationStep(0.2);
  streamers->SetTerminalSpeed(.01);
  streamers->Update();
  double range[2];
  range[0] = streamers->GetOutput()->GetPointData()->GetScalars()->GetRange()[0];
  range[1] = streamers->GetOutput()->GetPointData()->GetScalars()->GetRange()[1];

  vtkSmartPointer tubes =
    vtkSmartPointer::New();
  tubes->SetInputConnection(streamers->GetOutputPort());
  tubes->SetRadius(0.3);
  tubes->SetNumberOfSides(6);
  tubes->SetVaryRadius(0);

  vtkSmartPointer lut =
    vtkSmartPointer::New();
  lut->SetHueRange(.667, 0.0);
  lut->Build();

  vtkSmartPointer streamerMapper =
    vtkSmartPointer::New();
  streamerMapper->SetInputConnection(tubes->GetOutputPort());
  streamerMapper->SetScalarRange(range[0], range[1]);
  streamerMapper->SetLookupTable(lut);

  vtkSmartPointer streamerActor =
    vtkSmartPointer::New();
  streamerActor->SetMapper(streamerMapper);

实现结果图如下：