test(dicom): Add IDC test data and cases

packages/dicom/package.json

@@ -33,7 +33,7 @@
     "build:python:versionSync": "itk-wasm pnpm-script build:python:versionSync",
     "publish:python": "itk-wasm pnpm-script publish:python",
     "test": "pnpm test:data:download && pnpm build:gen:python && pnpm test:python",
-    "test:data:download": "dam download test/data test/data.tar.gz bafybeicfhacth6jwhtqd2caxwtepoydf54kv3zzr36zpoj7og5iuzptv7u https://data.kitware.com/api/v1/file/66c62d8faf422925a42121ab/download",
+    "test:data:download": "dam download test/data test/data.tar.gz bafybeiaqmwshl3vrcp5soxvmsez4nfhugcv7p432k6ndmb3jecspnvvv6u https://data.kitware.com/api/v1/file/6706def5fb903c47575aa6cc/download",
     "test:data:pack": "dam pack test/data test/data.tar.gz",
     "test:python:wasi": "itk-wasm pnpm-script test:python:wasi",
     "test:python:emscripten": "itk-wasm pnpm-script test:python:emscripten",

packages/dicom/python/itkwasm-dicom-wasi/test/test_read_segmentation.py

@@ -1,4 +1,5 @@
 from pathlib import Path
+import numpy as np
 from test_helper import compare_json
 
 testPathPrefix = '../../test/data/input/'
@@ -20,4 +21,27 @@ def test_read_segmentation():
     assert outputJSON is not None
     baselineJsonFile = 'dicom-images/SEG/MR_ref_3DSAGT2SPACE_tumor_seg.json'
     baselineJsonFilePath = Path(baselinePathPrefix, baselineJsonFile)
-    assert compare_json(baselineJsonFilePath, outputJSON)
+    assert compare_json(baselineJsonFilePath, outputJSON)
+
+def test_read_segmentation_idc1():
+    from itkwasm_dicom_wasi import read_segmentation
+    fileName = 'dicom-images/IDC/nlst/100010/1.2.840.113654.2.55.236467930500313421847662756581858562399/SEG_1.2.276.0.7230010.3.1.3.313263360.35955.1706319184.882151/0ec3f890-c11a-4b33-8a37-17a68a5c7545.dcm'
+    testFilePath = Path(testPathPrefix, fileName)
+    outputImage, outputJSON = read_segmentation(testFilePath)
+    assert outputImage is not None
+    assert outputImage.data is not None
+    assert outputImage.imageType.dimension == 3
+    assert outputImage.imageType.componentType == 'int16'
+    assert outputImage.imageType.pixelType == 'Scalar'
+    assert outputImage.imageType.components == 1
+
+    assert np.array_equal(outputImage.origin, [ -174.5, 174.316528, 9.04000854 ])
+    assert np.array_equal(outputImage.spacing, [ 0.683594, 0.683594, 2.5 ])
+    assert np.array_equal(np.array(outputImage.direction).flatten(), [ 1, 0, 0, 0, -1, 0, 0, 0, -1 ])
+    assert np.array_equal(outputImage.size, [ 512, 512, 137 ])
+    assert (outputImage.data.size == 35913728)
+
+    assert outputJSON is not None
+    baselineJsonFile = 'dicom-images/IDC/nlst/100010/1.2.840.113654.2.55.236467930500313421847662756581858562399/SEG_1.2.276.0.7230010.3.1.3.313263360.35955.1706319184.882151/metaInfo.json'
+    baselineJsonFilePath = Path(testPathPrefix, baselineJsonFile)
+    assert compare_json(baselineJsonFilePath, outputJSON)

packages/dicom/python/itkwasm-dicom-wasi/tests/common.py

@@ -3,4 +3,13 @@
 test_input_path = Path(__file__).parent / ".." / ".." / ".." / "test" / "data" / "input"
 test_baseline_path = Path(__file__).parent / ".." / ".." / ".." / "test" / "data" / "baseline"
 test_output_path = Path(__file__).parent / ".." / ".." / ".." / "test" / "data" / "output" / "python"
-test_output_path.mkdir(parents=True, exist_ok=True)
+test_output_path.mkdir(parents=True, exist_ok=True)
+
+def compare_rounded_float(a: float, b: float, n: int) -> bool:
+    return round(a, n) ==  round(b, n)
+
+def compare_array_float(a, b) -> bool:
+    for x in range(len(a)):
+        if not compare_rounded_float(a[x], b[x], 3):
+            return False
+    return True

packages/dicom/python/itkwasm-dicom-wasi/tests/test_read_image_dicom_file_series.py

@@ -1,8 +1,48 @@
-# Generated file. To retain edits, remove this comment.
-
 from itkwasm_dicom_wasi import read_image_dicom_file_series
 
-from .common import test_input_path, test_output_path
+from .common import test_input_path, test_output_path, compare_array_float
+
+from pathlib import Path
+import numpy as np
+from glob import glob
+
+testDataInputDirectory = Path("../../test/data/input").resolve()
 
 def test_read_image_dicom_file_series():
     pass
+
+def test_read_image_dicom_file_series_idc1():
+    nmFileName = "dicom-images/IDC/acrin_nsclc_fdg_pet/ACRIN-NSCLC-FDG-PET-134/1.3.6.1.4.1.14519.5.2.1.7009.2403.154904565437993902842316547208/NM_1.3.6.1.4.1.14519.5.2.1.7009.2403.484725606860278331095617627781/0d6c2de3-168b-4ea5-a1c8-c7d7438faa15.dcm"
+    testFilePath = Path(testDataInputDirectory, nmFileName)
+    output = read_image_dicom_file_series([testFilePath])
+    outputImage = output[0]
+    assert outputImage is not None
+    assert outputImage.data is not None
+    assert outputImage.imageType.dimension == 3
+    assert outputImage.imageType.componentType == 'uint16'
+    assert outputImage.imageType.pixelType == 'Scalar'
+    assert outputImage.imageType.components == 1
+
+    assert compare_array_float(outputImage.origin, [-204.602, -399.602, 1759.7])
+    assert compare_array_float(outputImage.spacing, [2.8125, 2.8125, 2])
+    assert compare_array_float(np.array(outputImage.direction).flatten(), [1, 0, 0, 0, 1, 0, 0, 0, -1])
+    assert np.array_equal(outputImage.size, [128, 128, 196])
+    assert (outputImage.data.size == 3211264)
+
+def test_read_image_dicom_file_series_idc2():
+    dirPath = 'dicom-images/IDC/nsclc_radiomics_genomics/LUNG3-49/1.3.6.1.4.1.32722.99.99.278496019127563640059579120768864824043/CT_1.3.6.1.4.1.32722.99.99.239963936032720978832553442140518002510'
+    testDicomSeriesFiles = glob(f"{Path(testDataInputDirectory, dirPath)}/*.dcm")
+    output = read_image_dicom_file_series(testDicomSeriesFiles)
+    outputImage = output[0]
+    assert outputImage is not None
+    assert outputImage.data is not None
+    assert outputImage.imageType.dimension == 3
+    assert outputImage.imageType.componentType == 'int16'
+    assert outputImage.imageType.pixelType == 'Scalar'
+    assert outputImage.imageType.components == 1
+
+    assert compare_array_float(outputImage.origin, [ -171, -102, 673.3 ])
+    assert compare_array_float(outputImage.spacing, [ 0.672, 0.672, 4.0])
+    assert compare_array_float(np.array(outputImage.direction).flatten(), [ 1, 0, 0, 0, 1, 0, 0, 0, -1 ])
+    assert np.array_equal(outputImage.size, [ 512, 512, 89 ])
+    assert (outputImage.data.size == 23330816)

packages/dicom/typescript/test/node/dcmqi.js

@@ -352,3 +352,35 @@ test('itk2dcm_makeSEG_seg_size', async t => {
     t.assert(r1.metrics.maximumDifference < 1e-8)
   }
 })
+
+// ========= IDC data tests =============
+test('IDC: DICOM segmentation', async t => {
+  const segFileName = 'dicom-images/IDC/nlst/100010/1.2.840.113654.2.55.236467930500313421847662756581858562399/SEG_1.2.276.0.7230010.3.1.3.313263360.35955.1706319184.882151/0ec3f890-c11a-4b33-8a37-17a68a5c7545.dcm'
+  const testFilePath = path.join(testPathPrefix, segFileName)
+  const output = await readSegmentationNode(testFilePath)
+  console.log(output)
+  console.log(output.segImage.imageType)
+  console.log(output.segImage.data)
+  console.log(JSON.stringify(output.metaInfo))
+
+  t.assert(output.segImage != null)
+  t.assert(output.segImage.data != null)
+  t.deepEqual(output.segImage.imageType, {
+    dimension: 3,
+    componentType: 'int16',
+    pixelType: 'Scalar',
+    components: 1
+  })
+  t.deepEqual(output.segImage.origin, [ -174.5, 174.316528, 9.04000854 ])
+  t.deepEqual(output.segImage.spacing, [ 0.683594, 0.683594, 2.5 ])
+  t.assert(arrayEquals(output.segImage.direction, [ 1, 0, 0, 0, -1, 0, 0, 0, -1 ]))
+  t.deepEqual(output.segImage.size, [ 512, 512, 137 ])
+  t.deepEqual(output.segImage.data.length, 35913728)
+
+  // The json file is simply generated from a previous call to readSegmentationNode. It is therefore, simply testing for regressions.
+  const baselineJsonFile = '/dicom-images/IDC/nlst/100010/1.2.840.113654.2.55.236467930500313421847662756581858562399/SEG_1.2.276.0.7230010.3.1.3.313263360.35955.1706319184.882151/metaInfo.json'
+  const baselineJsonFilePath = path.join(testPathPrefix, baselineJsonFile)
+  const baselineJsonFileBuffer = fs.readFileSync(baselineJsonFilePath)
+  const baselineJsonObject = JSON.parse(baselineJsonFileBuffer)
+  t.assert(JSON.stringify(baselineJsonObject) === JSON.stringify(output.metaInfo))
+})

packages/dicom/typescript/test/node/gdcm.js

@@ -14,6 +14,18 @@ function arrayEquals(a, b) {
   return (a.length === b.length && a.every((val, idx) => val === b[idx]))
 }
 
+function roundToThreePlaces(a) {
+  return Math.round((a + Number.EPSILON) * 1000) / 1000
+}
+
+function floatCompare(a, b) {
+  return (roundToThreePlaces(a) === roundToThreePlaces(b))
+}
+
+function floatCompareArray(a, b) {
+  return (a.length === b.length && a.every((val, idx) => floatCompare(val, b[idx])))
+}
+
 function verifyImage (t, image, expectedComponentType, expectedPixelType) {
   let componentType = IntTypes.Int16
   if (expectedComponentType) {
@@ -335,3 +347,48 @@ test('DICOM SOP: Nuclear Medicine Image.', async t => {
   ]))
   t.deepEqual(outputImage.size, [128, 128, 69])
 })
+
+// ========= IDC data tests =============
+test('IDC: Nuclear Medicine with negative SpacingBetweenSlices Test', async t => {
+  const nmFileName = 'dicom-images/IDC/acrin_nsclc_fdg_pet/ACRIN-NSCLC-FDG-PET-134/1.3.6.1.4.1.14519.5.2.1.7009.2403.154904565437993902842316547208/NM_1.3.6.1.4.1.14519.5.2.1.7009.2403.484725606860278331095617627781/0d6c2de3-168b-4ea5-a1c8-c7d7438faa15.dcm'
+  const testFilePath = path.join(testDataInputDirectory, nmFileName)
+  const output = await readImageDicomFileSeriesNode({inputImages: [testFilePath]})
+  t.assert(output)
+  const outputImage = output.outputImage
+  t.assert(outputImage != null)
+  t.assert(outputImage.imageType != null)
+  t.deepEqual(outputImage.imageType, {
+    dimension: 3,
+    componentType: 'uint16',
+    pixelType: 'Scalar',
+    components: 1
+  })
+  t.deepEqual(outputImage.origin, [ -204.60240003467, -399.60240003467, 1759.7 ])
+  t.deepEqual(outputImage.spacing, [ 2.8125, 2.8125, 2 ])
+  // Z-axis in direction matrix is flipped/negative due to the negative SpacingBetweenSlices
+  t.assert(arrayEquals(outputImage.direction, [ 1, 0, 0, 0, 1, 0, 0, 0, -1 ]))
+  t.deepEqual(outputImage.size, [ 128, 128, 196 ])
+  t.deepEqual(outputImage.data.length, 3211264)
+})
+
+test('IDC: CT with negative SpacingBetweenSlices Test', async t => {
+  const dirPath = 'dicom-images/IDC/nsclc_radiomics_genomics/LUNG3-49/1.3.6.1.4.1.32722.99.99.278496019127563640059579120768864824043/CT_1.3.6.1.4.1.32722.99.99.239963936032720978832553442140518002510'
+  const testDirPath = path.join(testDataInputDirectory, dirPath)
+  const testDicomSeriesFiles = glob.sync(`${testDirPath}/*.dcm`)
+  const output = await readImageDicomFileSeriesNode({inputImages: testDicomSeriesFiles})
+  t.assert(output)
+  const outputImage = output.outputImage
+  t.assert(outputImage != null)
+  t.assert(outputImage.imageType != null)
+  t.deepEqual(outputImage.imageType, {
+    dimension: 3,
+    componentType: 'int16',
+    pixelType: 'Scalar',
+    components: 1
+  })
+  t.assert(floatCompareArray(outputImage.origin, [ -171, -102, 673.300 ]))
+  t.assert(floatCompareArray(outputImage.spacing, [ 0.672, 0.672, 4.0]))
+  t.assert(arrayEquals(outputImage.direction, [ 1, 0, 0, 0, 1, 0, 0, 0, -1 ]))
+  t.deepEqual(outputImage.size, [ 512, 512, 89 ])
+  t.deepEqual(outputImage.data.length, 23330816)
+})