public void TestGetWindowsWithExplanations()
{
var windows = new[]
{
new VoiWindow(1, 2),
new VoiWindow(100, 200),
new VoiWindow(100.1, 200.2),
new VoiWindow(123.1, 456.2),
new VoiWindow(123.567890123, -23.567890123)
};
var dataset = new DicomAttributeCollection();
dataset[DicomTags.WindowCenter].SetStringValue(@"2\200\200.2\456.2\-23.567890123");
dataset[DicomTags.WindowWidth].SetStringValue(@"1\100\100.1\123.1\123.567890123");
dataset[DicomTags.WindowCenterWidthExplanation].SetStringValue(@"bob\alice\eve\james");
var actualWindows = VoiWindow.GetWindows(dataset).ToArray();
Assert.AreEqual(windows, actualWindows);
Assert.AreEqual("bob", actualWindows[0].Explanation);
Assert.AreEqual("alice", actualWindows[1].Explanation);
Assert.AreEqual("eve", actualWindows[2].Explanation);
Assert.AreEqual("james", actualWindows[3].Explanation);
Assert.AreEqual("", actualWindows[4].Explanation);
}
/// <summary>
/// Creates the <see cref="VolumeHeaderData"/> for the builder's source frames.
/// </summary>
/// <returns></returns>
public VolumeHeaderData BuildVolumeHeader()
{
if (_volumeHeaderData != null)
{
return(_volumeHeaderData);
}
PrepareFrames(_frames); // this also sorts the frames into order by slice location
// compute modality LUT parameters normalized for all frames
double normalizedSlope, normalizedIntercept;
var normalizedUnits = _frames[0].Frame.RescaleUnits;
ComputeNormalizedModalityLut(_frames, out normalizedSlope, out normalizedIntercept);
// determine an appropriate pixel padding value
var pixelPaddingValue = ComputePixelPaddingValue(_frames, normalizedSlope, normalizedIntercept);
// get the laterality of the anatomy being constructed
var laterality = _frames[0].Frame.Laterality;
// Construct a model SOP data source based on the first frame's DICOM header
var header = new VolumeHeaderData(_frames.Select(f => (IDicomAttributeProvider)f.Frame).ToList(), VolumeSize, VoxelSpacing, VolumePositionPatient, VolumeOrientationPatient, 16, 16, false, pixelPaddingValue, normalizedSlope, normalizedIntercept, normalizedUnits, laterality);
// determine how the normalized modality LUT affects VOI windows and update the header
VoiWindow.SetWindows(ComputeAggregateNormalizedVoiWindows(_frames, normalizedSlope, normalizedIntercept), header);
return(_volumeHeaderData = header);
}
/// <summary>
/// Creates and populates a <see cref="Volume"/> from the builder's source frames.
/// </summary>
public Volume Build()
{
PrepareFrames(_frames); // this also sorts the frames into order by slice location
// Construct a model SOP data source based on the first frame's DICOM header
var sopDataSourcePrototype = VolumeSopDataSourcePrototype.Create(_frames.Select(f => (IDicomAttributeProvider)f.Sop.DataSource).ToList(), 16, 16, false);
// compute normalized modality LUT
double normalizedSlope, normalizedIntercept;
ComputeNormalizedModalityLut(_frames, out normalizedSlope, out normalizedIntercept);
sopDataSourcePrototype[DicomTags.RescaleSlope].SetFloat64(0, normalizedSlope);
sopDataSourcePrototype[DicomTags.RescaleIntercept].SetFloat64(0, normalizedIntercept);
sopDataSourcePrototype[DicomTags.RescaleType] = _frames[0].Sop.DataSource[DicomTags.RescaleType].Copy();
sopDataSourcePrototype[DicomTags.Units] = _frames[0].Sop.DataSource[DicomTags.Units].Copy(); // PET series use this attribute to designate rescale units
// compute normalized VOI windows
VoiWindow.SetWindows(ComputeNormalizedVoiWindows(_frames, normalizedSlope, normalizedIntercept), sopDataSourcePrototype);
// compute the volume padding value
var pixelPaddingValue = ComputePixelPaddingValue(_frames, normalizedSlope, normalizedIntercept);
int minVolumeValue, maxVolumeValue;
var volumeArray = BuildVolumeArray(pixelPaddingValue, normalizedSlope, normalizedIntercept, out minVolumeValue, out maxVolumeValue);
var volume = new Volume(null, volumeArray, VolumeSize, VoxelSpacing, ImagePositionPatient, ImageOrientationPatient, sopDataSourcePrototype, pixelPaddingValue, _frames[0].Frame.SeriesInstanceUid, minVolumeValue, maxVolumeValue);
return(volume);
}
public void TestGetWindowsMissingWidths()
{
var dataset = new DicomAttributeCollection();
dataset[DicomTags.WindowCenter].SetStringValue(@"2\200\200.2\456.2\-23.567890123");
dataset[DicomTags.WindowWidth].SetEmptyValue();
var windows = VoiWindow.GetWindows(dataset).ToArray();
Assert.AreEqual(new VoiWindow[0], windows);
}
public void TestSetWindowsEmpty()
{
var windows = new VoiWindow[0];
var dataset = new DicomAttributeCollection();
VoiWindow.SetWindows(windows, dataset);
Assert.IsTrue(dataset[DicomTags.WindowCenter].IsEmpty);
Assert.IsTrue(dataset[DicomTags.WindowWidth].IsEmpty);
}
public FusionOverlayData(IEnumerable <Frame> overlaySource)
{
var frames = new List <IFrameReference>();
foreach (Frame frame in overlaySource)
{
frames.Add(frame.CreateTransientReference());
}
_frames = frames.AsReadOnly();
if (frames.Count > 0)
{
_voiWindows = new List <VoiWindow>(VoiWindow.GetWindows(frames[0].Sop.DataSource)).AsReadOnly();
}
}
public void TestExplanations()
{
var window0 = new VoiWindow(123.1, 456.2);
Assert.AreEqual(string.Empty, window0.Explanation);
var window1 = new VoiWindow(123.1, 456.2, null);
Assert.AreEqual(string.Empty, window1.Explanation);
Assert.AreEqual(window1, window0);
var window2 = new VoiWindow(123.1, 456.2, "explanation");
Assert.AreEqual("explanation", window2.Explanation);
Assert.AreEqual(window1, window2);
var window3 = new VoiWindow(4132, 324, "explanation");
Assert.AreNotEqual(window2, window3);
}
private static IEnumerable <VoiWindow> ComputeNormalizedVoiWindows(IImageSopProvider frame, double normalizedSlope, double normalizedIntercept)
{
var normalizedWindows = new List <VoiWindow>(VoiWindow.GetWindows(frame.Frame));
if (frame.ImageSop.Modality == @"PT" && frame.Frame.IsSubnormalRescale)
{
// for PET images with subnormal rescale, the VOI window will always be applied directly to the original stored pixel values
// since MPR will not have access to original stored pixel values, we compute the VOI window through original modality LUT and inverted normalized modality LUT
var normalizedVoiSlope = frame.Frame.RescaleSlope / normalizedSlope;
var normalizedVoiIntercept = (frame.Frame.RescaleIntercept - normalizedIntercept) / normalizedSlope;
for (var i = 0; i < normalizedWindows.Count; ++i)
{
var window = normalizedWindows[i]; // round the computed windows - the extra precision is not useful for display anyway
normalizedWindows[i] = new VoiWindow(Math.Ceiling(window.Width * normalizedVoiSlope), Math.Round(window.Center * normalizedVoiSlope + normalizedVoiIntercept), window.Explanation);
}
}
return(normalizedWindows);
}
public void TestBasics()
{
var window1 = new VoiWindow(123.1, 456.2);
Assert.AreEqual(123.1, window1.Width);
Assert.AreEqual(456.2, window1.Center);
Assert.AreEqual("123.10/456.20", window1.ToString());
Assert.IsFalse(window1.Equals(new object()));
var window2 = new VoiWindow(1.231, 456.2);
Assert.AreNotEqual(window1, window2);
var window3 = new VoiWindow(123.1, 4.562);
Assert.AreNotEqual(window1, window3);
var window4 = new VoiWindow(123.1, 456.2);
Assert.AreEqual(window1, window4);
}
public void TestGetWindowsMismatchedPairs()
{
var windows = new[]
{
new VoiWindow(1, 2),
new VoiWindow(100, 200),
new VoiWindow(100.1, 200.2),
new VoiWindow(123.1, 456.2)
};
var dataset = new DicomAttributeCollection();
dataset[DicomTags.WindowCenter].SetStringValue(@"2\200\200.2\456.2\-23.567890123");
dataset[DicomTags.WindowWidth].SetStringValue(@"1\100\100.1\123.1");
var actualWindows = VoiWindow.GetWindows(dataset).ToArray();
Assert.AreEqual(windows, actualWindows);
}
public FusionOverlayData(IEnumerable <Frame> overlaySource)
{
var frames = new List <IFrameReference>();
foreach (Frame frame in overlaySource)
{
frames.Add(frame.CreateTransientReference());
}
_frames = frames.AsReadOnly();
if (frames.Count > 0)
{
// TODO: should this VOI window be based on volume header's normalized VOI windows?
_voiWindows = new List <VoiWindow>(VoiWindow.GetWindows(frames[0].Frame)).AsReadOnly();
SourceSeriesInstanceUid = frames[0].Frame.SeriesInstanceUid;
FrameOfReferenceUid = frames[0].Frame.FrameOfReferenceUid;
Modality = frames[0].Sop.Modality;
}
}
public void TestExplanations()
{
var window0 = new VoiWindow(123.1, 456.2);
Assert.AreEqual(string.Empty, window0.Explanation);
var window1 = new VoiWindow(123.1, 456.2, null);
Assert.AreEqual(string.Empty, window1.Explanation);
Assert.AreEqual(window1, window0);
var window2 = new VoiWindow(123.1, 456.2, "explanation");
Assert.AreEqual("explanation", window2.Explanation);
Assert.AreEqual(window1, window2);
var window3 = new VoiWindow(4132, 324, "explanation");
Assert.AreNotEqual(window2, window3);
}
public void TestSetWindows()
{
var windows = new[]
{
new VoiWindow(1, 2),
new VoiWindow(100, 200),
new VoiWindow(100.1, 200.2),
new VoiWindow(123.1, 456.2),
new VoiWindow(123.567890123, -23.567890123)
};
var dataset = new DicomAttributeCollection();
VoiWindow.SetWindows(windows, dataset);
Assert.AreEqual(5, dataset[DicomTags.WindowCenter].Count);
Assert.AreEqual(dataset[DicomTags.WindowCenter].ToString(), @"2\200\200.2\456.2\-23.567890123");
Assert.AreEqual(5, dataset[DicomTags.WindowWidth].Count);
Assert.AreEqual(dataset[DicomTags.WindowWidth].ToString(), @"1\100\100.1\123.1\123.567890123");
}
public void TestBasics()
{
var window1 = new VoiWindow(123.1, 456.2);
Assert.AreEqual(123.1, window1.Width);
Assert.AreEqual(456.2, window1.Center);
Assert.AreEqual("123.10/456.20", window1.ToString());
Assert.IsFalse(window1.Equals(new object()));
var window2 = new VoiWindow(1.231, 456.2);
Assert.AreNotEqual(window1, window2);
var window3 = new VoiWindow(123.1, 4.562);
Assert.AreNotEqual(window1, window3);
var window4 = new VoiWindow(123.1, 456.2);
Assert.AreEqual(window1, window4);
}
public void TestSetWindowsWithExplanations()
{
var windows = new[]
{
new VoiWindow(1, 2, "bob"),
new VoiWindow(100, 200, "alice"),
new VoiWindow(100.1, 200.2, "eve"),
new VoiWindow(123.1, 456.2, "james"),
new VoiWindow(123.567890123, -23.567890123)
};
var dataset = new DicomAttributeCollection();
VoiWindow.SetWindows(windows, dataset);
Assert.AreEqual(5, dataset[DicomTags.WindowCenter].Count);
Assert.AreEqual(dataset[DicomTags.WindowCenter].ToString(), @"2\200\200.2\456.2\-23.567890123");
Assert.AreEqual(5, dataset[DicomTags.WindowWidth].Count);
Assert.AreEqual(dataset[DicomTags.WindowWidth].ToString(), @"1\100\100.1\123.1\123.567890123");
Assert.AreEqual(5, dataset[DicomTags.WindowCenterWidthExplanation].Count);
Assert.AreEqual(dataset[DicomTags.WindowCenterWidthExplanation].ToString(), @"bob\alice\eve\james\");
}
private static IEnumerable<VoiWindow> ComputeNormalizedVoiWindows(IList<IFrameReference> frames, double normalizedSlope, double normalizedIntercept)
{
var normalizedWindows = new List<VoiWindow>(VoiWindow.GetWindows(frames[0].Sop.DataSource));
if (frames[0].ImageSop.Modality == @"PT" && frames[0].Frame.IsSubnormalRescale)
{
// for PET images with subnormal rescale, the VOI window will always be applied directly to the original stored pixel values
// since MPR will not have access to original stored pixel values, we compute the VOI window through original modality LUT and inverted normalized modality LUT
var normalizedVoiSlope = frames[0].Frame.RescaleSlope/normalizedSlope;
var normalizedVoiIntercept = (frames[0].Frame.RescaleIntercept - normalizedIntercept)/normalizedSlope;
for (var i = 0; i < normalizedWindows.Count; ++i)
{
var window = normalizedWindows[i]; // round the computed windows - the extra precision is not useful for display anyway
normalizedWindows[i] = new VoiWindow(Math.Ceiling(window.Width*normalizedVoiSlope), Math.Round(window.Center*normalizedVoiSlope + normalizedVoiIntercept), window.Explanation);
}
}
return normalizedWindows;
}
public void TestSetWindowsEmpty()
{
var windows = new VoiWindow[0];
var dataset = new DicomAttributeCollection();
VoiWindow.SetWindows(windows, dataset);
Assert.IsTrue(dataset[DicomTags.WindowCenter].IsEmpty);
Assert.IsTrue(dataset[DicomTags.WindowWidth].IsEmpty);
}
