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20x 20x 20x 20x 20x 20x 20x 20x 20x 20x 20x 20x 1x 20x 20x 20x 160x 160x 160x 160x 160x 8x 160x 160x 160x 160x 160x 160x 160x 480x 149x 480x 151x 20x 7x 42x 2x 40x 7x 7x 4586x 4586x 1018070x 4586x 7x 21x 21x 21x 21x 21x 21x 21x 21x 21x 21x 21x 21x 7x 7x 9052x 9052x 7x 21x 7x 21x 21x 21x 21x 21x 7x 7x 362x 362x 65522x 7x 7x 7x 21x 7x 1x 7x 7x 7x 7x 7x 7x 7x 7x 7x 7x 1x | import { vec4, mat4 } from 'gl-matrix';
import macro, { vtkWarningMacro } from 'vtk.js/Sources/macros';
import vtkDataArray from 'vtk.js/Sources/Common/Core/DataArray';
import vtkMath from 'vtk.js/Sources/Common/Core/Math';
import vtkMatrixBuilder from 'vtk.js/Sources/Common/Core/MatrixBuilder';
import { VtkDataTypes } from 'vtk.js/Sources/Common/Core/DataArray/Constants';
import vtkBoundingBox from 'vtk.js/Sources/Common/DataModel/BoundingBox';
import vtkImageData from 'vtk.js/Sources/Common/DataModel/ImageData';
import vtkImageInterpolator from 'vtk.js/Sources/Imaging/Core/ImageInterpolator';
import vtkImagePointDataIterator from 'vtk.js/Sources/Imaging/Core/ImagePointDataIterator';
import {
ImageBorderMode,
InterpolationMode,
} from 'vtk.js/Sources/Imaging/Core/AbstractImageInterpolator/Constants';
import {
vtkInterpolationMathFloor,
vtkInterpolationMathRound,
vtkInterpolationMathClamp,
} from 'vtk.js/Sources/Imaging/Core/AbstractImageInterpolator/InterpolationInfo';
import Constants from 'vtk.js/Sources/Imaging/Core/ImageReslice/Constants';
const { SlabMode } = Constants;
const { vtkErrorMacro } = macro;
// ----------------------------------------------------------------------------
// vtkImageReslice methods
// ----------------------------------------------------------------------------
function vtkImageReslice(publicAPI, model) {
// Set our className
model.classHierarchy.push('vtkImageReslice');
const superClass = { ...publicAPI };
const indexMatrix = mat4.identity(new Float64Array(16));
let optimizedTransform = null;
function getImageResliceSlabTrap(tmpPtr, inComponents, sampleCount, f) {
const n = sampleCount - 1;
for (let i = 0; i < inComponents; i += 1) {
let result = tmpPtr[i] * 0.5;
for (let j = 1; j < n; j += 1) {
result += tmpPtr[i + j * inComponents];
}
result += tmpPtr[i + n * inComponents] * 0.5;
tmpPtr[i] = result * f;
}
}
function getImageResliceSlabSum(tmpPtr, inComponents, sampleCount, f) {
for (let i = 0; i < inComponents; i += 1) {
let result = tmpPtr[i];
for (let j = 1; j < sampleCount; j += 1) {
result += tmpPtr[i + j * inComponents];
}
tmpPtr[i] = result * f;
}
}
function getImageResliceCompositeMinValue(tmpPtr, inComponents, sampleCount) {
for (let i = 0; i < inComponents; i += 1) {
let result = tmpPtr[i];
for (let j = 1; j < sampleCount; j += 1) {
result = Math.min(result, tmpPtr[i + j * inComponents]);
}
tmpPtr[i] = result;
}
}
function getImageResliceCompositeMaxValue(tmpPtr, inComponents, sampleCount) {
for (let i = 0; i < inComponents; i += 1) {
let result = tmpPtr[i];
for (let j = 1; j < sampleCount; j += 1) {
result = Math.max(result, tmpPtr[i + j * inComponents]);
}
tmpPtr[i] = result;
}
}
function getImageResliceCompositeMeanValue(
tmpPtr,
inComponents,
sampleCount
) {
const f = 1.0 / sampleCount;
getImageResliceSlabSum(tmpPtr, inComponents, sampleCount, f);
}
function getImageResliceCompositeMeanTrap(tmpPtr, inComponents, sampleCount) {
const f = 1.0 / (sampleCount - 1);
getImageResliceSlabTrap(tmpPtr, inComponents, sampleCount, f);
}
function getImageResliceCompositeSumValue(tmpPtr, inComponents, sampleCount) {
const f = 1.0;
getImageResliceSlabSum(tmpPtr, inComponents, sampleCount, f);
}
function getImageResliceCompositeSumTrap(tmpPtr, inComponents, sampleCount) {
const f = 1.0;
getImageResliceSlabTrap(tmpPtr, inComponents, sampleCount, f);
}
publicAPI.getMTime = () => {
let mTime = superClass.getMTime();
Iif (model.resliceTransform) {
mTime = Math.max(mTime, model.resliceTransform.getMTime());
}
return mTime;
};
publicAPI.setResliceAxes = (resliceAxes) => {
if (!model.resliceAxes) {
model.resliceAxes = mat4.identity(new Float64Array(16));
}
if (!mat4.exactEquals(model.resliceAxes, resliceAxes)) {
mat4.copy(model.resliceAxes, resliceAxes);
publicAPI.modified();
return true;
}
return false;
};
publicAPI.requestData = (inData, outData) => {
// implement requestData
const input = inData[0];
Iif (!input) {
vtkErrorMacro('Invalid or missing input');
return;
}
// console.time('reslice');
// Retrieve output and volume data
const origin = input.getOrigin();
const inSpacing = input.getSpacing();
const dims = input.getDimensions();
const inScalars = input.getPointData().getScalars();
const inWholeExt = [0, dims[0] - 1, 0, dims[1] - 1, 0, dims[2] - 1];
const outOrigin = [0, 0, 0];
const outSpacing = [1, 1, 1];
const outWholeExt = [0, 0, 0, 0, 0, 0];
const outDims = [0, 0, 0];
const matrix = mat4.identity(new Float64Array(16));
if (model.resliceAxes) {
mat4.multiply(matrix, matrix, model.resliceAxes);
}
const imatrix = new Float64Array(16);
mat4.invert(imatrix, matrix);
const inCenter = [
origin[0] + 0.5 * (inWholeExt[0] + inWholeExt[1]) * inSpacing[0],
origin[1] + 0.5 * (inWholeExt[2] + inWholeExt[3]) * inSpacing[1],
origin[2] + 0.5 * (inWholeExt[4] + inWholeExt[5]) * inSpacing[2],
];
let maxBounds = null;
if (model.autoCropOutput) {
maxBounds = publicAPI.getAutoCroppedOutputBounds(input);
}
for (let i = 0; i < 3; i++) {
let s = 0; // default output spacing
let d = 0; // default linear dimension
let e = 0; // default extent start
let c = 0; // transformed center-of-volume
if (model.transformInputSampling) {
let r = 0.0;
for (let j = 0; j < 3; j++) {
c += imatrix[4 * j + i] * (inCenter[j] - matrix[4 * 3 + j]);
const tmp = matrix[4 * i + j] * matrix[4 * i + j];
s += tmp * Math.abs(inSpacing[j]);
d +=
tmp *
(inWholeExt[2 * j + 1] - inWholeExt[2 * j]) *
Math.abs(inSpacing[j]);
e += tmp * inWholeExt[2 * j];
r += tmp;
}
s /= r;
d /= r * Math.sqrt(r);
e /= r;
} else {
c = inCenter[i];
s = inSpacing[i];
d = (inWholeExt[2 * i + 1] - inWholeExt[2 * i]) * s;
e = inWholeExt[2 * i];
}
if (model.outputSpacing == null) {
outSpacing[i] = s;
} else {
outSpacing[i] = model.outputSpacing[i];
}
if (i >= model.outputDimensionality) {
outWholeExt[2 * i] = 0;
outWholeExt[2 * i + 1] = 0;
} else if (model.outputExtent == null) {
if (model.autoCropOutput) {
d = maxBounds[2 * i + 1] - maxBounds[2 * i];
}
outWholeExt[2 * i] = Math.round(e);
outWholeExt[2 * i + 1] = Math.round(
outWholeExt[2 * i] + Math.abs(d / outSpacing[i])
);
} else {
outWholeExt[2 * i] = model.outputExtent[2 * i];
outWholeExt[2 * i + 1] = model.outputExtent[2 * i + 1];
}
if (i >= model.outputDimensionality) {
outOrigin[i] = 0;
} else if (model.outputOrigin == null) {
if (model.autoCropOutput) {
// set origin so edge of extent is edge of bounds
outOrigin[i] = maxBounds[2 * i] - outWholeExt[2 * i] * outSpacing[i];
} else {
// center new bounds over center of input bounds
outOrigin[i] =
c -
0.5 * (outWholeExt[2 * i] + outWholeExt[2 * i + 1]) * outSpacing[i];
}
} else {
outOrigin[i] = model.outputOrigin[i];
}
outDims[i] = outWholeExt[2 * i + 1] - outWholeExt[2 * i] + 1;
}
let dataType = inScalars.getDataType();
if (model.outputScalarType) {
dataType = model.outputScalarType;
}
const numComponents = input
.getPointData()
.getScalars()
.getNumberOfComponents(); // or s.numberOfComponents;
const outScalarsData = macro.newTypedArray(
dataType,
outDims[0] * outDims[1] * outDims[2] * numComponents
);
const outScalars = vtkDataArray.newInstance({
name: 'Scalars',
values: outScalarsData,
numberOfComponents: numComponents,
});
// Update output
const output = vtkImageData.newInstance();
output.setDimensions(outDims);
output.setOrigin(outOrigin);
output.setSpacing(outSpacing);
if (model.outputDirection) {
output.setDirection(model.outputDirection);
}
output.getPointData().setScalars(outScalars);
publicAPI.getIndexMatrix(input, output);
let interpolationMode = model.interpolationMode;
model.usePermuteExecute = false;
Iif (model.optimization) {
if (
optimizedTransform == null &&
model.slabSliceSpacingFraction === 1.0 &&
model.interpolator.isSeparable() &&
publicAPI.isPermutationMatrix(indexMatrix)
) {
model.usePermuteExecute = true;
if (publicAPI.canUseNearestNeighbor(indexMatrix, outWholeExt)) {
interpolationMode = InterpolationMode.NEAREST;
}
}
}
model.interpolator.setInterpolationMode(interpolationMode);
let borderMode = ImageBorderMode.CLAMP;
borderMode = model.wrap ? ImageBorderMode.REPEAT : borderMode;
borderMode = model.mirror ? ImageBorderMode.MIRROR : borderMode;
model.interpolator.setBorderMode(borderMode);
const mintol = 7.62939453125e-6;
const maxtol = 2.0 * 2147483647;
let tol = 0.5 * model.border;
tol = borderMode === ImageBorderMode.CLAMP ? tol : maxtol;
tol = tol > mintol ? tol : mintol;
model.interpolator.setTolerance(tol);
model.interpolator.initialize(input);
publicAPI.vtkImageResliceExecute(input, output);
model.interpolator.releaseData();
outData[0] = output;
// console.timeEnd('reslice');
};
publicAPI.vtkImageResliceExecute = (input, output) => {
// const outDims = output.getDimensions();
const inScalars = input.getPointData().getScalars();
const outScalars = output.getPointData().getScalars();
let outPtr = outScalars.getData();
const outExt = output.getExtent();
const newmat = indexMatrix;
const outputStencil = null;
// multiple samples for thick slabs
const nsamples = Math.max(model.slabNumberOfSlices, 1);
// spacing between slab samples (as a fraction of slice spacing).
const slabSampleSpacing = model.slabSliceSpacingFraction;
// check for perspective transformation
const perspective = publicAPI.isPerspectiveMatrix(newmat);
// extra scalar info for nearest-neighbor optimization
let inPtr = inScalars.getData();
const inputScalarSize = 1; // inScalars.getElementComponentSize(); // inScalars.getDataTypeSize();
const inputScalarType = inScalars.getDataType();
const inComponents = inScalars.getNumberOfComponents(); // interpolator.GetNumberOfComponents();
const componentOffset = model.interpolator.getComponentOffset();
const borderMode = model.interpolator.getBorderMode();
const inDims = input.getDimensions();
const inExt = [0, inDims[0] - 1, 0, inDims[1] - 1, 0, inDims[2] - 1]; // interpolator->GetExtent();
const inInc = [0, 0, 0];
inInc[0] = inScalars.getNumberOfComponents();
inInc[1] = inInc[0] * inDims[0];
inInc[2] = inInc[1] * inDims[1];
const fullSize = inDims[0] * inDims[1] * inDims[2];
Iif (componentOffset > 0 && componentOffset + inComponents < inInc[0]) {
inPtr = inPtr.subarray(inputScalarSize * componentOffset);
}
let interpolationMode = InterpolationMode.NEAREST;
if (model.interpolator.isA('vtkImageInterpolator')) {
interpolationMode = model.interpolator.getInterpolationMode();
}
const convertScalars = null;
const rescaleScalars =
model.scalarShift !== 0.0 || model.scalarScale !== 1.0;
// is nearest neighbor optimization possible?
const optimizeNearest =
interpolationMode === InterpolationMode.NEAREST &&
borderMode === ImageBorderMode.CLAMP &&
!(
optimizedTransform != null ||
perspective ||
convertScalars != null ||
rescaleScalars
) &&
inputScalarType === outScalars.getDataType() &&
fullSize === inScalars.getNumberOfTuples() &&
model.border === true &&
nsamples <= 1;
// get pixel information
const scalarType = outScalars.getDataType();
const scalarSize = 1; // outScalars.getElementComponentSize() // outScalars.scalarSize;
const outComponents = outScalars.getNumberOfComponents();
// break matrix into a set of axes plus an origin
// (this allows us to calculate the transform Incrementally)
const xAxis = [0, 0, 0, 0];
const yAxis = [0, 0, 0, 0];
const zAxis = [0, 0, 0, 0];
const origin = [0, 0, 0, 0];
for (let i = 0; i < 4; ++i) {
xAxis[i] = newmat[4 * 0 + i];
yAxis[i] = newmat[4 * 1 + i];
zAxis[i] = newmat[4 * 2 + i];
origin[i] = newmat[4 * 3 + i];
}
// allocate an output row of type double
let floatPtr = null;
if (!optimizeNearest) {
floatPtr = new Float64Array(
inComponents * (outExt[1] - outExt[0] + nsamples)
);
}
const background = macro.newTypedArray(
inputScalarType,
model.backgroundColor
);
// set color for area outside of input volume extent
// void *background;
// vtkAllocBackgroundPixel(&background,
// self->GetBackgroundColor(), scalarType, scalarSize, outComponents);
// get various helper functions
const forceClamping =
interpolationMode > InterpolationMode.LINEAR ||
(nsamples > 1 && model.slabMode === SlabMode.SUM);
const convertpixels = publicAPI.getConversionFunc(
inputScalarType,
scalarType,
model.scalarShift,
model.scalarScale,
forceClamping
);
const setpixels = publicAPI.getSetPixelsFunc(
scalarType,
scalarSize,
outComponents,
outPtr
);
const composite = publicAPI.getCompositeFunc(
model.slabMode,
model.slabTrapezoidIntegration
);
// create some variables for when we march through the data
let idY = outExt[2] - 1;
let idZ = outExt[4] - 1;
const inPoint0 = [0.0, 0.0, 0.0, 0.0];
const inPoint1 = [0.0, 0.0, 0.0, 0.0];
// create an iterator to march through the data
const iter = vtkImagePointDataIterator.newInstance();
iter.initialize(output, outExt, model.stencil, null);
const outPtr0 = iter.getScalars(output, 0);
let outPtrIndex = 0;
const outTmp = macro.newTypedArray(
scalarType,
vtkBoundingBox.getDiagonalLength(outExt) * outComponents * 2
);
const interpolatedPtr = new Float64Array(inComponents * nsamples);
const interpolatedPoint = new Float64Array(inComponents);
for (; !iter.isAtEnd(); iter.nextSpan()) {
const span = iter.spanEndId() - iter.getId();
outPtrIndex = iter.getId() * scalarSize * outComponents;
Iif (!iter.isInStencil()) {
// clear any regions that are outside the stencil
const n = setpixels(outTmp, background, outComponents, span);
for (let i = 0; i < n; ++i) {
outPtr0[outPtrIndex++] = outTmp[i];
}
} else {
// get output index, and compute position in input image
const outIndex = iter.getIndex();
// if Z index increased, then advance position along Z axis
if (outIndex[2] > idZ) {
idZ = outIndex[2];
inPoint0[0] = origin[0] + idZ * zAxis[0];
inPoint0[1] = origin[1] + idZ * zAxis[1];
inPoint0[2] = origin[2] + idZ * zAxis[2];
inPoint0[3] = origin[3] + idZ * zAxis[3];
idY = outExt[2] - 1;
}
// if Y index increased, then advance position along Y axis
if (outIndex[1] > idY) {
idY = outIndex[1];
inPoint1[0] = inPoint0[0] + idY * yAxis[0];
inPoint1[1] = inPoint0[1] + idY * yAxis[1];
inPoint1[2] = inPoint0[2] + idY * yAxis[2];
inPoint1[3] = inPoint0[3] + idY * yAxis[3];
}
// march through one row of the output image
const idXmin = outIndex[0];
const idXmax = idXmin + span - 1;
if (!optimizeNearest) {
let wasInBounds = 1;
let isInBounds = 1;
let startIdX = idXmin;
let idX = idXmin;
const tmpPtr = floatPtr;
let pixelIndex = 0;
while (startIdX <= idXmax) {
for (; idX <= idXmax && isInBounds === wasInBounds; idX++) {
const inPoint2 = [
inPoint1[0] + idX * xAxis[0],
inPoint1[1] + idX * xAxis[1],
inPoint1[2] + idX * xAxis[2],
inPoint1[3] + idX * xAxis[3],
];
const inPoint3 = [0, 0, 0, 0];
let inPoint = inPoint2;
isInBounds = false;
let interpolatedPtrIndex = 0;
for (let sample = 0; sample < nsamples; ++sample) {
Iif (nsamples > 1) {
let s = sample - 0.5 * (nsamples - 1);
s *= slabSampleSpacing;
inPoint3[0] = inPoint2[0] + s * zAxis[0];
inPoint3[1] = inPoint2[1] + s * zAxis[1];
inPoint3[2] = inPoint2[2] + s * zAxis[2];
inPoint3[3] = inPoint2[3] + s * zAxis[3];
inPoint = inPoint3;
}
if (perspective) {
// only do perspective if necessary
const f = 1 / inPoint[3];
inPoint[0] *= f;
inPoint[1] *= f;
inPoint[2] *= f;
}
Iif (optimizedTransform !== null) {
// get the input origin and spacing for conversion purposes
const inOrigin = model.interpolator.getOrigin();
const inSpacing = model.interpolator.getSpacing();
const inInvSpacing = [
1.0 / inSpacing[0],
1.0 / inSpacing[1],
1.0 / inSpacing[2],
];
// apply the AbstractTransform if there is one
// TBD: handle inDirection
publicAPI.applyTransform(
optimizedTransform,
inPoint,
inOrigin,
inInvSpacing
);
}
if (model.interpolator.checkBoundsIJK(inPoint)) {
// do the interpolation
isInBounds = 1;
model.interpolator.interpolateIJK(inPoint, interpolatedPoint);
for (let i = 0; i < inComponents; ++i) {
interpolatedPtr[interpolatedPtrIndex++] =
interpolatedPoint[i];
}
}
}
Iif (interpolatedPtrIndex > inComponents) {
composite(
interpolatedPtr,
inComponents,
interpolatedPtrIndex / inComponents
);
}
for (let i = 0; i < inComponents; ++i) {
tmpPtr[pixelIndex++] = interpolatedPtr[i];
}
// set "was in" to "is in" if first pixel
wasInBounds = idX > idXmin ? wasInBounds : isInBounds;
}
// write a segment to the output
const endIdX = idX - 1 - (isInBounds !== wasInBounds);
const numpixels = endIdX - startIdX + 1;
let n = 0;
if (wasInBounds) {
Iif (outputStencil) {
outputStencil.insertNextExtent(startIdX, endIdX, idY, idZ);
}
if (rescaleScalars) {
publicAPI.rescaleScalars(
floatPtr,
inComponents,
idXmax - idXmin + 1,
model.scalarShift,
model.scalarScale
);
}
Iif (convertScalars) {
convertScalars(
floatPtr.subarray(startIdX * inComponents),
outTmp,
inputScalarType,
inComponents,
numpixels,
startIdX,
idY,
idZ
);
n = numpixels * outComponents * scalarSize;
} else {
n = convertpixels(
outTmp,
floatPtr.subarray(startIdX * inComponents),
outComponents,
numpixels
);
}
} else {
n = setpixels(outTmp, background, outComponents, numpixels);
}
for (let i = 0; i < n; ++i) {
outPtr0[outPtrIndex++] = outTmp[i];
}
startIdX += numpixels;
wasInBounds = isInBounds;
}
} else {
// optimize for nearest-neighbor interpolation
const inPtrTmp0 = inPtr;
const outPtrTmp = outPtr;
const inIncX = inInc[0] * inputScalarSize;
const inIncY = inInc[1] * inputScalarSize;
const inIncZ = inInc[2] * inputScalarSize;
const inExtX = inExt[1] - inExt[0] + 1;
const inExtY = inExt[3] - inExt[2] + 1;
const inExtZ = inExt[5] - inExt[4] + 1;
let startIdX = idXmin;
let endIdX = idXmin - 1;
let isInBounds = false;
const bytesPerPixel = inputScalarSize * inComponents;
for (let iidX = idXmin; iidX <= idXmax; iidX++) {
const inPoint = [
inPoint1[0] + iidX * xAxis[0],
inPoint1[1] + iidX * xAxis[1],
inPoint1[2] + iidX * xAxis[2],
];
const inIdX = vtkInterpolationMathRound(inPoint[0]) - inExt[0];
const inIdY = vtkInterpolationMathRound(inPoint[1]) - inExt[2];
const inIdZ = vtkInterpolationMathRound(inPoint[2]) - inExt[4];
if (
inIdX >= 0 &&
inIdX < inExtX &&
inIdY >= 0 &&
inIdY < inExtY &&
inIdZ >= 0 &&
inIdZ < inExtZ
) {
if (!isInBounds) {
// clear leading out-of-bounds pixels
startIdX = iidX;
isInBounds = true;
const n = setpixels(
outTmp,
background,
outComponents,
startIdX - idXmin
);
for (let i = 0; i < n; ++i) {
outPtr0[outPtrIndex++] = outTmp[i];
}
}
// set the final index that was within input bounds
endIdX = iidX;
// perform nearest-neighbor interpolation via pixel copy
let offset = inIdX * inIncX + inIdY * inIncY + inIdZ * inIncZ;
// when memcpy is used with a constant size, the compiler will
// optimize away the function call and use the minimum number
// of instructions necessary to perform the copy
switch (bytesPerPixel) {
case 1:
outPtr0[outPtrIndex++] = inPtrTmp0[offset];
break;
case 2:
case 3:
case 4:
case 8:
case 12:
case 16:
for (let i = 0; i < bytesPerPixel; ++i) {
outPtr0[outPtrIndex++] = inPtrTmp0[offset + i];
}
break;
default: {
// TODO: check bytes
let oc = 0;
do {
outPtr0[outPtrIndex++] = inPtrTmp0[offset++];
} while (++oc !== bytesPerPixel);
break;
}
}
} else Eif (isInBounds) {
// leaving input bounds
break;
}
}
// clear trailing out-of-bounds pixels
outPtr = outPtrTmp;
const n = setpixels(
outTmp,
background,
outComponents,
idXmax - endIdX
);
for (let i = 0; i < n; ++i) {
outPtr0[outPtrIndex++] = outTmp[i];
}
Iif (outputStencil && endIdX >= startIdX) {
outputStencil.insertNextExtent(startIdX, endIdX, idY, idZ);
}
}
}
}
};
/**
* The transform matrix supplied by the user converts output coordinates
* to input coordinates.
* To speed up the pixel lookup, the following function provides a
* matrix which converts output pixel indices to input pixel indices.
* This will also concatenate the ResliceAxes and the ResliceTransform
* if possible (if the ResliceTransform is a 4x4 matrix transform).
* If it does, this->OptimizedTransform will be set to nullptr, otherwise
* this->OptimizedTransform will be equal to this->ResliceTransform.
* @param {vtkImageData} input
* @param {vtkImageData} output
* @returns
*/
publicAPI.getIndexMatrix = (input, output) => {
const transform = mat4.identity(new Float64Array(16));
optimizedTransform = null;
if (model.resliceAxes) {
mat4.copy(transform, model.resliceAxes);
}
Iif (model.resliceTransform) {
if (model.resliceTransform.isA('vtkHomogeneousTransform')) {
mat4.multiply(transform, model.resliceTransform.getMatrix(), transform);
} else {
// TODO
vtkWarningMacro('Non homogeneous transform have not yet been ported');
}
}
// the outMatrix takes OutputData indices to OutputData coordinates,
const outMatrix = output.getIndexToWorld();
mat4.multiply(transform, transform, outMatrix);
// the inMatrix takes InputData coordinates to InputData indices
// the optimizedTransform requires data coords, not index coords, as its input
if (optimizedTransform == null) {
const inMatrix = input.getWorldToIndex();
mat4.multiply(transform, inMatrix, transform);
}
mat4.copy(indexMatrix, transform);
return indexMatrix;
};
publicAPI.getAutoCroppedOutputBounds = (input) => {
const inOrigin = input.getOrigin();
const inSpacing = input.getSpacing();
const inDirection = input.getDirection();
const dims = input.getDimensions();
const inWholeExt = [0, dims[0] - 1, 0, dims[1] - 1, 0, dims[2] - 1];
const matrix = new Float64Array(16);
if (model.resliceAxes) {
mat4.invert(matrix, model.resliceAxes);
} else E{
mat4.identity(matrix);
}
let transform = null;
Iif (model.resliceTransform) {
transform = model.resliceTransform.getInverse();
}
let imageTransform = null;
if (!vtkMath.isIdentity3x3(inDirection)) {
imageTransform = vtkMatrixBuilder
.buildFromRadian()
.translate(inOrigin[0], inOrigin[1], inOrigin[2])
.multiply3x3(inDirection)
.translate(-inOrigin[0], -inOrigin[1], -inOrigin[2])
.invert()
.getMatrix();
}
const bounds = [
Number.MAX_VALUE,
-Number.MAX_VALUE,
Number.MAX_VALUE,
-Number.MAX_VALUE,
Number.MAX_VALUE,
-Number.MAX_VALUE,
];
const point = [0, 0, 0, 0];
for (let i = 0; i < 8; ++i) {
point[0] = inOrigin[0] + inWholeExt[i % 2] * inSpacing[0];
point[1] =
inOrigin[1] + inWholeExt[2 + (Math.floor(i / 2) % 2)] * inSpacing[1];
point[2] =
inOrigin[2] + inWholeExt[4 + (Math.floor(i / 4) % 2)] * inSpacing[2];
point[3] = 1.0;
if (imageTransform) {
vec4.transformMat4(point, point, imageTransform);
}
Iif (model.resliceTransform) {
transform.transformPoint(point, point);
}
vec4.transformMat4(point, point, matrix);
const f = 1.0 / point[3];
point[0] *= f;
point[1] *= f;
point[2] *= f;
for (let j = 0; j < 3; ++j) {
if (point[j] > bounds[2 * j + 1]) {
bounds[2 * j + 1] = point[j];
}
if (point[j] < bounds[2 * j]) {
bounds[2 * j] = point[j];
}
}
}
return bounds;
};
publicAPI.getDataTypeMinMax = (dataType) => {
switch (dataType) {
case 'Int8Array':
return { min: -128, max: 127 };
case 'Int16Array':
return { min: -32768, max: 32767 };
case 'Uint16Array':
return { min: 0, max: 65535 };
case 'Int32Array':
return { min: -2147483648, max: 2147483647 };
case 'Uint32Array':
return { min: 0, max: 4294967295 };
case 'Float32Array':
return { min: -1.2e38, max: 1.2e38 };
case 'Float64Array':
return { min: -1.2e38, max: 1.2e38 };
case 'Uint8Array':
case 'Uint8ClampedArray':
default:
return { min: 0, max: 255 };
}
};
publicAPI.clamp = (outPtr, inPtr, numscalars, n, min, max) => {
const count = n * numscalars;
for (let i = 0; i < count; ++i) {
outPtr[i] = vtkInterpolationMathClamp(inPtr[i], min, max);
}
return count;
};
publicAPI.convert = (outPtr, inPtr, numscalars, n) => {
const count = n * numscalars;
for (let i = 0; i < count; ++i) {
outPtr[i] = Math.round(inPtr[i]);
}
return count;
};
publicAPI.getConversionFunc = (
inputType,
dataType,
scalarShift,
scalarScale,
forceClamping
) => {
let useClamping = forceClamping;
if (
dataType !== VtkDataTypes.FLOAT &&
dataType !== VtkDataTypes.DOUBLE &&
!forceClamping
) {
const inMinMax = publicAPI.getDataTypeMinMax(inputType);
let checkMin = (inMinMax.min + scalarShift) * scalarScale;
let checkMax = (inMinMax.max + scalarShift) * scalarScale;
const outMinMax = publicAPI.getDataTypeMinMax(dataType);
const outputMin = outMinMax.min;
const outputMax = outMinMax.max;
Iif (checkMin > checkMax) {
const tmp = checkMax;
checkMax = checkMin;
checkMin = tmp;
}
useClamping = checkMin < outputMin || checkMax > outputMax;
}
Iif (
useClamping &&
dataType !== VtkDataTypes.FLOAT &&
dataType !== VtkDataTypes.DOUBLE
) {
const minMax = publicAPI.getDataTypeMinMax(dataType);
const clamp = (outPtr, inPtr, numscalars, n) =>
publicAPI.clamp(outPtr, inPtr, numscalars, n, minMax.min, minMax.max);
return clamp;
}
return publicAPI.convert;
};
publicAPI.set = (outPtr, inPtr, numscalars, n) => {
const count = numscalars * n;
for (let i = 0; i < n; ++i) {
outPtr[i] = inPtr[i];
}
return count;
};
publicAPI.set1 = (outPtr, inPtr, numscalars, n) => {
outPtr.fill(inPtr[0], 0, n);
return n;
};
publicAPI.getSetPixelsFunc = (dataType, dataSize, numscalars, dataPtr) =>
numscalars === 1 ? publicAPI.set1 : publicAPI.set;
publicAPI.getCompositeFunc = (slabMode, slabTrapezoidIntegration) => {
let composite = null;
// eslint-disable-next-line default-case
switch (slabMode) {
case SlabMode.MIN:
composite = getImageResliceCompositeMinValue;
break;
case SlabMode.MAX:
composite = getImageResliceCompositeMaxValue;
break;
case SlabMode.MEAN:
if (slabTrapezoidIntegration) {
composite = getImageResliceCompositeMeanTrap;
} else {
composite = getImageResliceCompositeMeanValue;
}
break;
case SlabMode.SUM:
if (slabTrapezoidIntegration) {
composite = getImageResliceCompositeSumTrap;
} else {
composite = getImageResliceCompositeSumValue;
}
break;
}
return composite;
};
publicAPI.applyTransform = (newTrans, inPoint, inOrigin, inInvSpacing) => {
inPoint[3] = 1;
vec4.transformMat4(inPoint, inPoint, newTrans);
inPoint[0] -= inOrigin[0];
inPoint[1] -= inOrigin[1];
inPoint[2] -= inOrigin[2];
inPoint[0] *= inInvSpacing[0];
inPoint[1] *= inInvSpacing[1];
inPoint[2] *= inInvSpacing[2];
};
publicAPI.rescaleScalars = (
floatData,
components,
n,
scalarShift,
scalarScale
) => {
const m = n * components;
for (let i = 0; i < m; ++i) {
floatData[i] = (floatData[i] + scalarShift) * scalarScale;
}
};
publicAPI.isPermutationMatrix = (matrix) => {
for (let i = 0; i < 3; i++) {
if (matrix[4 * i + 3] !== 0) {
return false;
}
}
if (matrix[4 * 3 + 3] !== 1) {
return false;
}
for (let j = 0; j < 3; j++) {
let k = 0;
for (let i = 0; i < 3; i++) {
if (matrix[4 * j + i] !== 0) {
k++;
}
}
if (k !== 1) {
return false;
}
}
return true;
};
// TODO: to move in vtkMath and add tolerance
publicAPI.isIdentityMatrix = (matrix) => {
for (let i = 0; i < 4; ++i) {
for (let j = 0; j < 4; ++j) {
if ((i === j ? 1.0 : 0.0) !== matrix[4 * j + i]) {
return false;
}
}
}
return true;
};
publicAPI.isPerspectiveMatrix = (matrix) =>
matrix[4 * 0 + 3] !== 0 ||
matrix[4 * 1 + 3] !== 0 ||
matrix[4 * 2 + 3] !== 0 ||
matrix[4 * 3 + 3] !== 1;
publicAPI.canUseNearestNeighbor = (matrix, outExt) => {
// loop through dimensions
for (let i = 0; i < 3; i++) {
let j;
for (j = 0; j < 3; j++) {
if (matrix[4 * j + i] !== 0) {
break;
}
}
if (j >= 3) {
return false;
}
let x = matrix[4 * j + i];
let y = matrix[4 * 3 + i];
if (outExt[2 * j] === outExt[2 * j + 1]) {
y += x * outExt[2 * i];
x = 0;
}
const fx = vtkInterpolationMathFloor(x, 0).error;
const fy = vtkInterpolationMathFloor(y, 0).error;
if (fx !== 0 || fy !== 0) {
return false;
}
}
return true;
};
}
// ----------------------------------------------------------------------------
// Object factory
// ----------------------------------------------------------------------------
const DEFAULT_VALUES = {
transformInputSampling: true,
autoCropOutput: false,
outputDimensionality: 3,
outputSpacing: null, // automatically computed if null
outputOrigin: null, // automatically computed if null
outputDirection: null, // identity if null
outputExtent: null, // automatically computed if null
outputScalarType: null,
wrap: false, // don't wrap
mirror: false, // don't mirror
border: true, // apply a border
interpolationMode: InterpolationMode.NEAREST, // only NEAREST supported so far
slabMode: SlabMode.MIN,
slabTrapezoidIntegration: false,
slabNumberOfSlices: 1,
slabSliceSpacingFraction: 1,
optimization: false, // not supported yet
scalarShift: 0, // for rescaling the data
scalarScale: 1,
backgroundColor: [0, 0, 0, 0],
resliceAxes: null,
// resliceTransform: null,
interpolator: vtkImageInterpolator.newInstance(),
usePermuteExecute: false, // no supported yet
};
// ----------------------------------------------------------------------------
export function extend(publicAPI, model, initialValues = {}) {
Object.assign(model, DEFAULT_VALUES, initialValues);
// Make this a VTK object
macro.obj(publicAPI, model);
// Also make it an algorithm with one input and one output
macro.algo(publicAPI, model, 1, 1);
macro.setGet(publicAPI, model, [
'outputDimensionality',
'outputScalarType',
'scalarShift',
'scalarScale',
'transformInputSampling',
'autoCropOutput',
'wrap',
'mirror',
'border',
'interpolationMode',
'resliceTransform',
'slabMode',
'slabTrapezoidIntegration',
'slabNumberOfSlices',
'slabSliceSpacingFraction',
]);
macro.setGetArray(publicAPI, model, ['outputOrigin', 'outputSpacing'], 3);
macro.setGetArray(publicAPI, model, ['outputExtent'], 6);
macro.setGetArray(publicAPI, model, ['outputDirection'], 9);
macro.setGetArray(publicAPI, model, ['backgroundColor'], 4);
macro.get(publicAPI, model, ['resliceAxes']);
// Object specific methods
vtkImageReslice(publicAPI, model);
}
// ----------------------------------------------------------------------------
export const newInstance = macro.newInstance(extend, 'vtkImageReslice');
// ----------------------------------------------------------------------------
export default { newInstance, extend, ...Constants };
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