NAMIC Wiki:DTI:DICOM for DWI and DTI - Revision history

Hjmjohnson: /* Related Links */

2022-12-20T03:23:51Z

2021-03-11T15:28:12Z

Private vendor: Toshiba

2021-03-11T15:16:55Z

Validation Datasets

2021-03-11T15:14:47Z

2021-03-11T15:10:58Z

DICOM for DWI

2021-03-11T14:51:24Z

Private vendor: Canon

2020-08-27T14:52:21Z

Private vendor: Canon

2020-04-14T14:22:42Z

Private vendor: Siemens

2019-02-25T20:55:18Z

DICOM for estimated diffusion tensors

2019-02-25T19:13:38Z

Private vendor: Philips

← Older revision		Revision as of 03:23, 20 December 2022
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	[http://www.na-mic.org/Wiki/index.php/DTI:Acquisition Randy's DTI Acquisition notes]		[http://www.na-mic.org/Wiki/index.php/DTI:Acquisition Randy's DTI Acquisition notes]
		+
		+	== Python psuedocode ==
		+
		+	```python
		+
		+	def get_bvalue(dicom_header_info) -> str:
		+	"""
		+	Extract bvalue from pydicom information
		+	`dicom_header_info = dicom.read_file(dicom_file_name, stop_before_pixels=True)`
		+	:param dicom_header_info: A pydicom object
		+	:return: a string representing the BValue
		+	"""
		+	# bvalue tags from private fields provided by https://www.nmr.mgh.harvard.edu/~greve/dicom-unpack
		+	private_tags_map = {
		+	"Standard": (0x0018, 0x9087),
		+	"UHI": (0x0065, 0x1009),
		+	"GE": (0x0043, 0x1039),
		+	"Siemens": (0x0019, 0x100C),
		+	"Siemens_historical": (0x0029, 0x1010), # NOT SUPPORTED
		+	"Siemens_old": (0x0019, 0x000C),
		+	"Philips": (0x2001, 0x1003)
		+	# "Toshiba" : # Uses (0x0018, 0x9087) standard
		+	}
		+	for k, v in private_tags_map.items():
		+	if v in dicom_header_info:
		+	# This decoding of bvalues follows the NAMIC conventions defined at
		+	# https://www.na-mic.org/wiki/NAMIC_Wiki:DTI:DICOM_for_DWI_and_DTI
		+	dicom_element = dicom_header_info[v]
		+	if k == "GE":
		+	large_number_modulo_for_GE = 100000
		+	value = dicom_element.value[0] % large_number_modulo_for_GE
		+	elif dicom_element.VR == "OB":
		+	value = dicom_element.value.decode("utf-8")
		+	else:
		+	value = dicom_element.value
		+	print(f"Found BValue at {v} for {k}, {value} of type {dicom_element.VR}")
		+	return str(value)
		+	return "-1234"
		+	```

@@ Line 277: / Line 277: @@
+}
 </pre>
 == DICOM for estimated diffusion tensors ==

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 Sample datasets are available for most manufacturers that provide concrete examples for their storage of diffusion information:
-- [https://www.nitrc.org/plugins/mwiki/index.php/dcm2nii:MainPage#Diffusion_Tensor_Imaging dcm2niix NITRC page]
+* [https://www.nitrc.org/plugins/mwiki/index.php/dcm2nii:MainPage#Diffusion_Tensor_Imaging dcm2niix NITRC page includes GE, Philips and Siemens DICOMs]
-- [https://github.com/neurolabusc/dcm_qa_canon_enh Canon Classic DICOMs]
+* [https://github.com/neurolabusc/dcm_qa_canon_enh Canon Classic DICOMs]
-- [https://github.com/neurolabusc/dcm_qa_canon_enh Canon Enhanced DICOMs]
+* [https://github.com/neurolabusc/dcm_qa_canon_enh Canon Enhanced DICOMs]
-- [https://osf.io/brvak/ Siemens Mosaic DICOMs]
+* [https://github.com/neurolabusc/dcm_qa_philips Philips DICOMs]
+* [https://osf.io/brvak/ Siemens Mosaic DICOMs]
+* [https://github.com/neurolabusc/dcm_qa_uih UIH DICOMs]
 == Related Links ==

@@ Line 295: / Line 295: @@
   implementing a new mechanism and navigating through a more general
   structure.
 == Related Links ==

@@ Line 13: / Line 13: @@
 9117 SQ 1 MR Diffusion Sequence
 9147 CS 1 Diffusion Anisotropy Type
 These are defined in [ftp://medical.nema.org/medical/dicom/final/sup49_ft.pdf Supplement 49]. In particular see section C.8.12.5.9 "MR Diffusion Macro" on pages 94 and 95.
@@ Line 21: / Line 27: @@
 * The definition of "Diffusion Gradient Orientation" implies that the measurement frame is exactly the identity transform.
-* There appears to be no means of recording the full B-matrix when it is known. This is not an issue for any NAMIC datasets, but can arise in small-bore imaging.
+* While one can encode the B-matrix, it is [https://github.com/rordenlab/dcm2niix/issues/265 underspecified to store the polarity of the b-vector]. This makes it insufficient for tools like [https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/eddy#eddy_--_a_tool_for_correcting_eddy_currents_and_movements_in_diffusion_data FSL's eddy] which leverage the fact that polar opposite b-vectors should have identical true signal yet differ due to eddy currents (and therefore artifacts can be modeled and removed).
 === Private vendor: Canon ===

@@ Line 25: / Line 25: @@
 === Private vendor: Canon ===
-For Canon (né Toshiba) scanners the gradient direction is stored in the text-based image comments fields. For older systems, the DiffusionBValue (0018,9087) tag may be omitted for images where the b-value is equal to zero:
+For Canon (né Toshiba) scanners saving classic 2D DICOM images, the gradient direction is stored in the text-based image comments fields. For older systems, the DiffusionBValue (0018,9087) tag may be omitted for images where the b-value is equal to zero. Be aware that the gradient direction stored in the comment field may not take into account the phase encoding polarity, so it may not be accurate. Example data illustrating this problem is [https://github.com/neurolabusc/dcm_qa_canon available]. For this reason, one should concern using a tool like GradFlipTest to determine the gradient direction. A sample for this type of data might be:
 * (0018,9087) FD 1500                            #   8, 1 DiffusionBValue
 * (0020,4000) LT [b=1500(0.445,0.000,0.895)]     #  26, 1 ImageComments
 === Private vendor: GE ===

@@ Line 77: / Line 77: @@
 === Private vendor: Siemens ===
-Siemens Vida XA10 and XA11 systems will use the recommended public tags (described above) when exporting as enhanced DICOM.
+Siemens software is reported by Series, Generation, Major Version and Minor Version. Therefore, 'VB17' data was created on a V-series, B-generation, version 1.7. Historically, all Siemens systems were V-series (Trio, Skyra, Prisma, etc), so people might just say data was from 'B17'.
-−
-Some Siemens systems, including the Vida XA11 exporting to classic DICOM format will populate the private tags (0019,100c) and (0019,100e) for B-value and B-vector respectively. Here is an example:
+For Siemens V-series systems from the B-generation onward (around 2005), the most reliable way to read diffusion gradients is from the [https://nipy.org/nibabel/dicom/siemens_csa.html CSA header]. Specially, for the 'DiffusionGradientDirection' and 'B_value' tags.
-  (0019,100c) IS [1500]
+  (0019,100c) IS [10]                                               # 2,1 B_value
-  (0019,100e) FD [0.41\-0.40-0.81]
+ (0019,100d) CS [BMATRIX ]                                         # 8,1 DiffusionDirectionality
 A Siemens DICOM Conformance Statement is available at

@@ Line 203: / Line 203: @@
 === Private vendor: Philips ===
-Be aware that Philips will store derived diffusion images (e.g. isotropic images) in the same series as the raw data. Since derived images will disrupt processing, and one will be able to generate better derived after processing (e.g. de-Gibbs, de-noise, eddy correction) one typically wants to identify and discard these derived images.
+Be aware that Philips will store derived diffusion images (e.g. isotropic images) in the same series as the raw data. Derived images will disrupt processing. Further, one will be able to generate better derived images after processing (e.g. de-Gibbs, de-noise, eddy correction). Therefore, one typically wants to identify and discard these derived images.
 Many Philips images use the following private tags for diffusion weighted images