Hello,
I'm trying to create a nifti file from some older (2006-2009) dicom files
using mri_convert, and I'm having some difficulty. Part of this is
uncertainty about the dicom files in question. The files were collected on
Siemens scanner between 2006 and 2009, and I *believe* they should be in
Siemens dicom format. They came off the magnet without a .dcm extension, if
I recall correctly, but I used Brain Voyager to rename the dicom files (I
believe all it does is re-title them to reflect the acquisition order, but
I'm not 100% sure about that - that could be part of the problem). Running
mri_convert to create a nifti file from the first file in each of the
sequences I have yields the error I have copied below.
<redacted> bits are there for anonymity, I don't think those fields relate
to the problem. The main problem with this call seems to be that some
fields regarding the image position are not read correctly, so the affine
transform has nans in it.
I also tried calling mri_convert -it dicom, which succeeded, but created an
image that was of shape (384, 384, 1, 202). I don't know why that call to
mri_convert doesn't correctly recognize that the images in the dicoms are,
in fact, mosaic images (in the first call, there was an "IsMosaic" field
that was set to 0, but I'm pretty sure it should be 1 or True or whatever);
the resulting 4D array should be (64, 64, 32, 202).
However, the image that the second call created may have had a correct
affine transform (at least there were no nans) - to check on it in python,
I called:
nii = nibabel.load(file_name)
nii.affine
... and got:
array([[ -3.5 , -0. , -0. , 672.67797852],
[ -0. , -3.5 , -0. , 690.59564209],
[ 0. , 0. , 3. , -52.07869339],
[ 0. , 0. , 0. , 1. ]])
... So, now I'm a little stuck. -it seimens did not help, gave me the same
error as below (same for -it siemens_dicom). I don't fully understand how
to possibly override the bad info, or how to tell mri_convert where to find
the correct info, or how to tell if I'm just out of luck with this whole
endeavor.
mri_convert --version spits out "stable5", which might be a slightly older
version.
Any help will be much appreciated.
Cheers,
Mark
Error message:
----
Getting Series No
Scanning Directory
INFO: Found 993 files in old_data/ML_Localizers/Raw_Retinotopy_05_29_09
INFO: Scanning for Series Number 21
INFO: found 202 files in series
INFO: loading series header info.
# <there were lots of these error lines, one for each file in the series; i
think these are due to the space between the subject ID, which I've
redacted, and -0021-0001-00001.dcm > #
error: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeD
efault.xctoolchain/usr/bin/strings: invalid decimal number in flag:
-0021-0001-00001.dcm
Usage: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeD
efault.xctoolchain/usr/bin/strings [-] [-a] [-o] [-t format] [-number] [-n
number] [[-arch <arch_flag>] ...] [--] [file ...]
WARNING: file <redacted> -0021-0001-00001.dcm does not contain a Siemens
ASCII header
has this file been anonymized?
Proceeding as best as I can ...
INFO: (384 384 1), nframes = 202, ismosaic=0
PE Dir COL COL
FileName <redacted>/<redacted> -0021-0001-00001.dcm
Identification
NumarisVer syngo MR B15
ScannerModel TrioTim
PatientName <redacted>
Date and time
StudyDate <redacted>
StudyTime 105825.156000
SeriesTime 122023.890000
AcqTime 122021.700000
Acquisition parameters
PulseSeq *epfid2d1_64
Protocol <redacted>
PhEncDir COL
EchoNo 1
FlipAngle 90
EchoTime 30
InversionTime -1
RepetitionTime 2000
PhEncFOV 0
ReadoutFOV 0
Image information
RunNo 20
SeriesNo 21
ImageNo 1
NImageRows 384
NImageCols 384
NFrames 202
SliceArraylSize 0
IsMosaic 0
ImgPos 672.6780 690.5956 -52.0787
VolRes 3.5000 3.5000 3.0000
VolDim 384 384 1
Vc -1.0000 -0.0000 0.0000
Vr -0.0000 -1.0000 0.0000
Vs nan nan nan
VolCenter nan nan nan
TransferSyntaxUID 1.2.840.10008.1.2.1
UseSliceScaleFactor 0 (slice 0: 1)
INFO: no Siemens slice order reversal detected (good!).
TR=2000.00, TE=30.00, TI=-1.00, flip angle=90.00
i_ras = (-1, -0, 0)
j_ras = (-0, -1, 0)
k_ras = (nan, nan, nan)
Reslicing using trilinear interpolation
MRIresample(): error inverting matrix; determinant is nan, matrix is:
-3.500 -0.000 nan nan;
-0.000 -3.500 nan nan;
0.000 0.000 nan nan;
0.000 0.000 0.000 1.000;
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