# Convert STL file to high-resolution TIFF stack

**URL:** <https://discourse.slicer.org/t/convert-stl-file-to-high-resolution-tiff-stack/15949>\
**Category:** Support\
**Tags:** segmentation, python\
**Created:** [February 11, 2021, 2:42am UTC](https://discourse.slicer.org/t/convert-stl-file-to-high-resolution-tiff-stack/15949 "2021-02-11T02:42:10Z")\
**Posts on this page:** 1\
**Showing post:** 8

<div class="post-metadata">

**Author:** ![lassoan](https://sea2.discourse-cdn.com/flex002/user_avatar/discourse.slicer.org/lassoan/32/13_2.png) [@lassoan](https://discourse.slicer.org/u/lassoan)\
**Post date:** [February 12, 2021, 1:27am UTC](https://discourse.slicer.org/t/convert-stl-file-to-high-resolution-tiff-stack/15949/8 "2021-02-12T01:27:59Z")

</div>

By default, when you import a module, the image extents are increased to include the entire model, essentially undoing the limit that you set on the reference geometry. You can disable this by changing a conversion parameter.

After some cleanup and simplification of the code, here is a complete working version:

```python
inputModelFile = r"c:\Users\andra\OneDrive\SpinePhantom2Model.stl"
outputDir = r"c:\tmp\20210211-model-rasterization"
outputVolumeLabelValue = 255
inPlaneResolutionDpi = 400
planeThicknessMm = 0.1
outputVolumeMarginMm = [0, 0, 0] # mm of buffer before/after and around

import math
import numpy as np
import sys
try:
    import imageio
except ImportError:
    pip_install("imageio")

imageSpacingMm = [25.4/inPlaneResolutionDpi, 25.4/inPlaneResolutionDpi, planeThicknessMm]
inputModel = slicer.util.loadModel(inputModelFile)
bounds = np.zeros(6)
inputModel.GetBounds(bounds)
imageSize = [int((math.ceil(bounds[axis*2+1] - bounds[axis*2] + 2 * outputVolumeMarginMm[axis]))/imageSpacingMm[axis]) for axis in range(3) ]
imageOrigin = [bounds[axis*2] - outputVolumeMarginMm[axis] for axis in range(3) ]
sliceImageData = vtk.vtkImageData()
sliceImageData.SetDimensions(imageSize[0], imageSize[1], 1)
sliceImageData.AllocateScalars(vtk.VTK_UNSIGNED_CHAR, 1)
sliceImageData.GetPointData().GetScalars().Fill(0)
sliceNode = slicer.mrmlScene.AddNewNodeByClass("vtkMRMLLabelMapVolumeNode")
sliceNode.SetOrigin(imageOrigin)
sliceNode.SetSpacing(imageSpacingMm)
sliceNode.SetAndObserveImageData(sliceImageData)
sliceNode.CreateDefaultDisplayNodes()
seg = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLSegmentationNode')
seg.SetReferenceImageGeometryParameterFromVolumeNode(sliceNode)
# restrict rasterization to the reference geometry (single frame at a time)
seg.GetSegmentation().SetConversionParameter("Crop to reference image geometry", "1")
seg.GetSegmentation().SetSourceRepresentationName("Closed surface")
slicer.modules.segmentations.logic().ImportModelToSegmentationNode(inputModel, seg)
segmentId = seg.GetSegmentation().GetNthSegmentID(0)
seg.CreateBinaryLabelmapRepresentation()

for sliceIndex in range(imageSize[2]):
    sliceNode.SetOrigin(imageOrigin[0], imageOrigin[1], imageOrigin[2] + sliceIndex * imageSpacingMm[2])
    seg.SetReferenceImageGeometryParameterFromVolumeNode(sliceNode)
    seg.GetSegmentation().CreateRepresentation('Binary labelmap', True) # Force recreating binary labelmap representation immediately
    outputSliceImageArray = np.squeeze(slicer.util.arrayFromSegmentBinaryLabelmap(seg, segmentId)).astype('uint8')
    outputSliceImageArray[outputSliceImageArray>0] = outputVolumeLabelValue
    filename = f'{outputDir}/slice_{sliceIndex:03}.tif'
    result = imageio.imwrite(filename, outputSliceImageArray)
    print(filename)
    slicer.app.processEvents() # update console

```

It takes a while to generate thousands of slices if conversion is done for one slice at a time. Probably you can make it faster if you convert 10-20 frames at a time instead.

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_[View the full topic](https://discourse.slicer.org/t/convert-stl-file-to-high-resolution-tiff-stack/15949)._