I want to convert dicom files to nifty files, but I got this problem.

This is the source code:

converter = Dcm2niix()
converter.inputs.source_dir = source_dir
converter.inputs.compression = 9
converter.inputs.output_dir = output_dir
converter.inputs.out_filename = 'DWI'
converter.inputs.bids_format = False
converter.run()

Could you please help me figure it out?

Hi,

I am trying to convert MRI's from Dicom to Nifti

Was going swimmingly well till I got this message

Found 1422 DICOM file(s)
DICOM images may be missing, expected 70 spatial locations per volume, but found 1422 slices.
Slice positions repeated, but number of slices (1422) not divisible by number of repeats (21): missing images?
Hint: expected 70 locations
Warning: Interslice distance varies in this volume (incompatible with NIfTI format).
Unable to equalize slice distances: slice order not consistently ascending.
First spatial position repeated 21 times

Can anyone please explain what this means and what I can do about it?

Using MRIcroGL

Thanks

I've downloaded the COBRE datasets (that contains control AND schizophrenia data only) from Schizoconnect. It is my first time to train model with .nii file. I am confused about how to make a model from .nii dataset. So, can anyone tell me the complete steps from extracting dataset file to predicting schizophrenia? That is, after extracting, I got 90 subjects (of no_known_disorder) and similarily for schizophrenia data, and in each subject there are multiple files, so which one I have to select for training model only .nii or others too?, How to make two folders so that one folder contains only .nii files of schizophrenia and second folder contains only no_known_disorder (i.e. healthy/control files of .nii), now how to preprocess data, how to read and open/display nii files using python script, then how to divide whole data into training and test set and then apply simple CNN model to get predictions that is, whether person is schizophrenic or not? Please help me to solve this issue using python script.

How to get images from the DICOM (.dcm) files. I'm using COBRE data that contains numerous .nii and .dcm (DICOM) files, and each DICOM file contains 30 scans of the brain. I want the PNG/JPG of each scan that is 30 images (in PNG/JPG) from a single DICOM file to use as an input for the CNN model. How to get it?

Hello,

I am trying to convert some old DICOM files to nifti, but have gotten an error warning me that my slice times may be corrupted. Upon investigation, many of the slice timings are greater than my TR. The issue does not appear to be due to incorrect units (eg TR in seconds and slice timings in milliseconds). I have provided the JSON contents below and happy to provide additional information if helpful. Any suggestions on how to approach this issue would be greatly appreciated!

JSON contents:
{
  "AcquisitionMatrixPE": 98,
  "AcquisitionNumber": 1,
  "AcquisitionTime": "09:36:53.452500",
  "BandwidthPerPixelPhaseEncode": 14.789,
  "BaseResolution": 98,
  "BodyPartExamined": "BRAIN",
  "CoilCombinationMethod": "Sum of Squares",
  "ConsistencyInfo": "N4_VD13A_LATEST_20120616",
  "ConversionSoftware": "dcm2niix",
  "ConversionSoftwareVersion": "v1.0.20220720",
  "DerivedVendorReportedEchoSpacing": 0.000689978,
  "DeviceSerialNumber": "45306",
  "DwellTime": 2.9e-06,
  "EchoTime": 0.033,
  "EchoTrainLength": 86,
  "EffectiveEchoSpacing": 0.000689978,
  "FlipAngle": 65,
  "HeudiconvVersion": "0.12.2",
  "ImageComments": "SMS_MGH_V2.1; MB=5; FOVshift=4; K_PE=3; K_RO=3; CCR=1; LeakBlockOn;",
  "ImageOrientationPatientDICOM": [1, 0, 0, 0, 1, 0],
  "ImageOrientationText": "Tra",
  "ImageType": [
    "ORIGINAL",
    "PRIMARY",
    "M",
    "ND",
    "MOSAIC"
],
  "ImagingFrequency": 123.232,
  "InPlanePhaseEncodingDirectionDICOM": "COL",
  "InstitutionAddress": 
  "InstitutionName": 
  "InstitutionalDepartmentName": 
  "MRAcquisitionType": "2D",
  "MagneticFieldStrength": 3,
  "Manufacturer": "Siemens",
  "ManufacturersModelName": "Skyra",
  "MatrixCoilMode": "SENSE",
  "Modality": "MR",
  "NonlinearGradientCorrection": false,
  "PartialFourier": 0.875,
  "PatientPosition": "HFS",
  "PercentPhaseFOV": 100,
  "PercentSampling": 100,
  "PhaseEncodingDirection": "j-",
  "PhaseEncodingSteps": 86,
  "PhaseResolution": 1,
  "PixelBandwidth": 1760,
  "ProcedureStepDescription": 
  "ProtocolName": "Bold_sms_StressTask_run_1",
  "PulseSequenceDetails": "%CustomerSeq%\\ep2d_bold_sms_mgh_v22",
  "ReceiveCoilActiveElements": "HEA;HEP",
  "ReceiveCoilName": "Head_32",
  "ReconMatrixPE": 98,
  "RepetitionTime": 1.25,
  "SAR": 0.401866,
  "ScanOptions": "PFP\\FS",
  "ScanningSequence": "EP",
  "SequenceName": "epfSM2d1_98",
  "SequenceVariant": "SK",
  "SeriesDescription": "Bold_sms_StressTask_run_1",
  "SeriesNumber": 3,
  "ShimSetting": [1950, 7762, -14938, 328, -99, 573, 520, 81],
  "SliceThickness": 2,
  "SliceTiming": [0, 3.1575, 0.085, 3.24, 0.1675, 3.3225, 0.25, 3.4075, 0.3325, 3.49, 0.415, 3.5725, 0.5, 3.655, 0.5825, 3.7375, 0.665, 3.8225, 0.7475, 3.905, 0.8325, 3.9875, 0.915, 4.07, 0.9975, 4.155, 1.08, 4.2375, 1.1625, 4.32, 1.2475, 4.4025, 1.33, 4.485, 1.4125, 4.57, 1.495, 4.6525, 1.58, 4.735, 1.6625, 4.8175, 1.745, 4.9025, 1.8275, 4.985, 1.9125, 5.0675, 1.995, 5.15, 2.0775, 5.2325, 2.16, 5.3175, 2.2425, 5.4, 2.3275, 5.4825, 2.41, 5.565, 2.4925, 5.65, 2.575, 5.7325, 2.66, 5.815, 2.7425, 5.8975, 2.825, 5.98, 2.9075, 6.065, 2.99, 6.1475, 3.075],
  "SoftwareVersions": "syngo MR D13",
  "SpacingBetweenSlices": 2,
  "StationName": "221L-3T",
  "TaskName": "stress1",
  "TotalReadoutTime": 0.0669278,
  "TxRefAmp": 311.453}

Hello Chris and the `dcm2niix` community,

I'm reaching out for guidance on a challenge we're currently facing. We are working with abdomen MR DICOM images intended for segmentation model training. We've observed that some of our DICOM datasets, which are composed images (resulting from upper and lower acquisition sequences combined together), exhibit inconsistent actual slice spacing. I understand that the NIfTI format typically assumes equidistant slices.

Having not tried the `dcm2niix` conversion for these particular datasets yet, I'd like to be proactive and gather insights:

1. Is it possible to convert such DICOM images with varying slice spacings to NIfTI using `dcm2niix` without running into issues?
2. If challenges are anticipated, do you have any recommendations or best practices for preprocessing these DICOM images prior to conversion?
3. Are there specific flags or parameters in `dcm2niix` that might help in ensuring an accurate conversion for these datasets?

Thank you for your time and expertise. We truly appreciate any insights you can provide.

Chenglin

Hello,

I'm encountering issues while trying to convert DICOM files to NII files using dcm2niix(version v1.0.20230411  Clang14.0.0 ARM (64-bit MacOS)), due to some warning messages. I'm processing data from two different centers, and they are showing different warning messages.

For the first center, which used a MAGNETOM Trio scanner, I'm getting the following warnings for image types of EPI, REST and DTI.

Warning: Weird CSA 'ProtocolSliceNumber' (System/Miscellaneous/ImageNumbering reversed): VALIDATE SLICETIMING AND BVECS

Warning: Assuming mosaics saved in reverse order due to 'sSliceArray.ucImageNumb'

For the second center, which used a MAGNETOM Vida scanner, I'm getting the following warning for EPI and DTI data:

EPI and DTI appear to have

CSA slice timing based on 2nd volume, 1st volume corrupted (CMRR bug, range 8350..9085, TR=835 ms) / CSA slice timing based on 2nd volume, 1st volume corrupted (CMRR bug, range 44800..47837.5, TR=3200 ms

Even though these warnings are appearing, the NII files seem to open correctly. I will be using EPI and DTI images, so is it safe to proceed with the analysis as is? If there might be an issue, what kind of processing can be done? I've attached the JSON files as well.

Thanks in advance.

Hi experts, 

Hello experts,

I'm struggling with converting diffusion images from DICOM to NII format for data obtained from a Philips Intera MRI. The issue is that my bvec files are mostly zeros.

I get the following warnings: 

Warning: Volume number does not vary (0019,10A2; 0020,0100; 2005,1063; 2005,1413), assuming meaningful instance number (0020,0013).
Error: Check sorted order: 4D dataset has 34 volumes, but volume index ranges from 33..3960
Warning: Isotropic DWI series, all bvecs are zero (issue 405)
Warning: Volume 1 appears to be derived image ADC/Isotropic (non-zero b-value with zero vector length)

......

Warning: Saving 34 DTI gradients. Validate vectors (image slice orientation not reported, e.g. 2001,100B)

Any tips or guidance on this matter would be greatly appreciated.

Thanks in advance,

María José Torres

Hi there. 

I am transforming dicom to nifti. I get following output: 

data_type INT16

dim1 256

dim2 256

dim3 186

dim4 1

datatype 4

pixdim1 1.000000

pixdim2 1.000000

pixdim3 1.000000

pixdim4 0.008136

cal_max 0.000000

cal_min 0.000000

file_type NIFTI-1+; 

but I need this dimensionality:

data_type INT16

dim1 64

dim2 64

dim3 30

dim4 196

datatype 4

pixdim1 3.437500

pixdim2 3.437500

pixdim3 5.000000

pixdim4 2.000000

cal_max 9897.000000

cal_min 0.000000

file_type NIFTI-1+

Can someone help me please? Thanks

Hello everyone,

I am currently in the process of validating GE DTI scans using different Patient Positions (HFS, FFS), oblique vs. non-oblique acquisitions and reversed slice orders. When checking the 'geCorrectBvecs()' function I came across the 'sliceDir' variable. I found the function 'headerDcm2NiiSForm()' that is returning sliceDir as follows: 0=unknown,1=sag,2=coro,3=axial,-=reversed slices

I struggle in understanding what exactly is happening in the C code and how the sliceDir is determined from the DICOM header information. Could anyone help me out, in particular for the settings used by GE?

The scans that I have are in PhaseEncoding 'COL' either HFS or FFS and slice order either from inferior to superior or from superior to inferior (by ticking the "reverse slice order" check box on the scanner GUI when setting up the FOV).

Assuming sliceDir to be axial (sliceDir=3), I would expect a bvec file with reversed z component for those scans using the reversed slice order from the 'geCorrectBvecs()' function. (Please be aware that FFS is currently not handled by geCorrectBvecs() but Jaemin Shin from GE recently made changes in the dcm2niix development branch that I am testing).

I hope my questions are understandable... I appreciate any help or thoughts on this. Thanks!

Hello,

I have used dcm2niix (v1.0.20210317) to convert ADNI DWI data collected on Siemens, GE, and Philips scanners to NIFTI format. I am trying to determine the phase encoding direction of each scan to use the eddy tool for distortion correction. 

I am aware from a post on neurostars that only the phase encoding axis can be estimated for Philips (i,j,k) but not the polarity due to missing information from meta-data (https://neurostars.org/t/bids-fmriprep-s...). So it seems, I will have to get that information from ADNI, rather than the JSON files.

For the Siemens and GE files, a majority of phase encoding directions are "j", but some are noted as "j-" in the JSON files. Given that this is an axial acquisition, "j" should map onto the y-axis (PA). I then used fslhd to confirm this by extracting the sform_code and sform_yorient information. For all subjects (regardless of whether PhaseEncodingDirection was coded as j or j-), the sform_yorient is Posterior-to-Anterior. 

For subjects with reverse polarity ("j-"), should the sform_yorient instead be coded as Anterior-to-Posterior? Ultimately, I'm wondering if there is any information from fslhd that should code the change in acquisition polarity (e.g., "j-" swapped PE direction)?

Thank you,

Jenna

• Warning: Unable to compute slice times for GE Diffusion
• GE DTI directions require head first supine acquisition