<div dir="ltr"><div><div><div><div><div>Dear Philip,<br><br></div>Thank you very much for your reply.<br><br></div>I actually do have 10 b0 volumes, all at the beginning of the sequence. In the other (60) volumes, b=1500 s / mm^2.</div><div><br></div>Below I report the content of a subject schemefile.</div><div>Any help in understanding these warnings is welcome.<br>Thank you in advance.</div><div><br></div><div># Scheme file created by fsl2scheme<br>VERSION: BVECTOR<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.000000 0.000000 0.000000 0.000E00<br> 0.999991 -0.002709 -0.003328 1.500E03<br> 0.588135 -0.376556 0.715753 1.500E03<br> 0.892734 0.019598 -0.450158 1.500E03<br> 0.726299 -0.414097 -0.548647 1.500E03<br> -0.151352 0.964975 0.214280 1.500E03<br> 0.121489 0.774265 0.621091 1.500E03<br> -0.406026 -0.412028 0.815706 1.500E03<br> 0.210309 0.751788 -0.624968 1.500E03<br> 0.091726 -0.970107 -0.224676 1.500E03<br> -0.132289 -0.030859 0.990731 1.500E03<br> -0.142083 -0.748737 0.647460 1.500E03<br> -0.634146 0.748399 0.194312 1.500E03<br> 0.082006 0.970910 -0.224963 1.500E03<br> 0.103423 -0.023671 -0.994356 1.500E03<br> 0.296816 0.384548 -0.874084 1.500E03<br> -0.211531 -0.804065 -0.555638 1.500E03<br> 0.334280 -0.038782 0.941676 1.500E03<br> -0.806717 -0.587107 0.067183 1.500E03<br> 0.337078 -0.749386 0.569912 1.500E03<br> 0.589137 -0.763698 -0.263976 1.500E03<br> -0.093194 -0.467293 -0.879177 1.500E03<br> -0.531563 -0.431045 -0.729137 1.500E03<br> -0.371728 -0.926260 -0.062133 1.500E03<br> 0.314806 0.926206 0.207460 1.500E03<br> -0.681450 0.442704 0.582785 1.500E03<br> -0.031949 -0.966060 0.256335 1.500E03<br> -0.333768 0.746743 0.575303 1.500E03<br> -0.572075 0.028252 0.819715 1.500E03<br> 0.267140 -0.749790 -0.605352 1.500E03<br> -0.935653 0.187361 -0.299080 1.500E03<br> 0.891010 0.308050 0.333477 1.500E03<br> -0.882715 0.037017 0.468448 1.500E03<br> 0.548703 0.586259 0.596008 1.500E03<br> -0.353933 -0.017304 -0.935111 1.500E03<br> 0.413948 -0.901465 0.126523 1.500E03<br> -0.734925 0.003790 -0.678137 1.500E03<br> -0.738542 0.612670 -0.281410 1.500E03<br> -0.252386 0.409535 0.876688 1.500E03<br> -0.917477 0.375620 0.130940 1.500E03<br> -0.257583 0.764310 -0.591169 1.500E03<br> -0.591164 0.433719 -0.680010 1.500E03<br> 0.891935 -0.187383 0.411509 1.500E03<br> 0.681841 0.141939 0.717598 1.500E03<br> -0.881847 -0.307877 -0.357152 1.500E03<br> -0.624994 -0.695934 -0.353637 1.500E03<br> 0.895463 -0.433038 -0.103076 1.500E03<br> -0.165112 0.416292 -0.894114 1.500E03<br> -0.507833 -0.776310 0.373429 1.500E03<br> 0.108396 -0.444105 0.889394 1.500E03<br> 0.884028 0.432542 -0.177206 1.500E03<br> 0.595488 0.026520 -0.802927 1.500E03<br> 0.698417 0.696777 0.163451 1.500E03<br> -0.391447 0.901331 -0.185395 1.500E03<br> -0.760528 -0.399642 0.511745 1.500E03<br> 0.214359 0.397610 0.892164 1.500E03<br> 0.373301 -0.382391 -0.845236 1.500E03<br> 0.734139 -0.613391 0.291192 1.500E03<br> -0.987401 -0.142973 0.067802 1.500E03<br> 0.531000 0.805078 -0.264362 1.500E03<br> 0.662204 0.469604 -0.583916 1.500E03<br><br></div><br></div><div><div> <br><div><br><br></div></div></div></div><div class="gmail_extra"><br><div class="gmail_quote">2018-01-18 16:57 GMT+01:00 Cook, Philip <span dir="ltr"><<a href="mailto:cookpa@pennmedicine.upenn.edu" target="_blank">cookpa@pennmedicine.upenn.edu</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
<div style="word-wrap:break-word">
<div>Do you have any b=0 measurements in your data? I think the problem is that it's trying to normalize the data by dividing each measurement by the mean b=0 measurement. The non-linear tensor fit only operates on the non-zero b-values. If there is
no b=0, the results might look reasonable in terms of anisotropy, but the scale could be off.</div>
<div><br>
</div>
<div>If you have a very small minimum b-value (eg, 5 s / mm^2), you could try setting that to 0 in the scheme file. Then it would normalize by those measurements, and the estimated S_0 would be very close to correct.</div>
<div><br>
</div>
<div><br>
<div>
<blockquote type="cite"><div><div class="h5">
<div>On Jan 18, 2018, at 10:29 AM, Marie Amelie <<a href="mailto:mariamelie.sque@gmail.com" target="_blank">mariamelie.sque@gmail.com</a>> wrote:</div>
<br class="m_6153274617876216541Apple-interchange-newline">
</div></div><div><div><div class="h5">
<div dir="ltr">
<div>
<div>Dear camino users,<br>
<br>
</div>
I am using camino to fit the tensor model (nonlinear optimization, constrained to be positive semi-definite) on dMRI data with the following command:<br>
<br>
modelfit -inputfile dwi.Bfloat -schemefile schemefile.scheme -inversion 2 -bgmask mask_Bfloat.nii.gz -maskdatatype float -outputfile dt.Bdouble<br>
</div>
<div><br>
</div>
<div>The process globally seems to work fine: the tensor fitting and then the derived scalar maps (produced as indicated in camino's DTI tutorial) are ok both at the visual inspection and by comparing their values to the ones computed by a previous
tensor fitting with another tool. However in the terminal I am seeing many instances of these warnings:</div>
<div><br>
</div>
<div>Jan 17, 2018 10:50:35 AM imaging.DW_Scheme normalizeData<br>
WARNING: Can't use normalization constant NaN</div>
<div><br>
</div>
<div>My question is: can you explain me why I am seeing these warnings? Can I trust my tensor fit despite these warnings? Again, scalar maps and their values look globally fine.<br>
</div>
<div>Could it be related to my brain/backgound mask? It is actually rather conservative (i.e. tends to exclude some voxels of the brain rather than include background voxels), but I can't exclude that in some instances it might also include some background
(even if perhaps not that frequently). <br>
</div>
<div>I am a new camino user, I apologize in advance if this is a basic question.<br>
</div>
<div><br>
</div>
<div>------------------------------<wbr>------------------------------<wbr>----------------<br>
</div>
<div>Here follows additional information.</div>
<div><br>
</div>
<div>Before the tensor fit, I performed an eddy-current correction (MRtrix' dwipreproc) and then did with camino:</div>
<div>fsl2scheme -bvecfile bvec_rot.txt -bvalfile bval.txt > schemefile.scheme<br>
</div>
<div>image2voxel -4dimage dwi.nii.gz -outputfile dwi.Bfloat<br>
</div>
<div><br>
</div>
<div><br>
</div>
<div>For completeness, I report here that I also get some instances of this error:</div>
<div>Jan 17, 2018 10:50:32 AM misc.LoggedException logException<br>
WARNING: Exception in thread "main" class optimizers.MarquardtMinimiserE<wbr>xception: Singular Matrix in gaussj - 2
<br>
at optimizers.MarquardtMinimiser.<wbr>gaussj(MarquardtMinimiser.java<wbr>:362)<br>
at optimizers.MarquardtMinimiser.<wbr>mrqmin(MarquardtMinimiser.java<wbr>:231)<br>
at optimizers.MarquardtMinimiser.<wbr>minimise(MarquardtMinimiser.ja<wbr>va:156)<br>
at inverters.NonLinearDT_Inversio<wbr>n.invert(NonLinearDT_Inversion<wbr>.java:135)<br>
at apps.ModelFit.execute(ModelFit<wbr>.java:156)<br>
at apps.EntryPoint.main(EntryPoin<wbr>t.java:290)<br>
</div>
<div><br>
</div>
<div>but from the camino FAQ webpage I think I understood their meaning.</div>
<div><br>
</div>
<div>I am running it on a Ubuntu 16.04 machine. <br>
</div>
<div>The git log of my camino version is:<br>
</div>
<div>commit af55b0acd7895b7d1dafa040df60c4<wbr>94369b138a<br>
Author: Philip Cook <<a href="mailto:cookpa@mail.med.upenn.edu" target="_blank">cookpa@mail.med.upenn.edu</a>><br>
Date: Fri Oct 6 12:00:17 2017 -0400<br>
<br>
ENH: Allow non-zero unweighted measurements for dtspd<br>
<br>
------------------------------<wbr>------------------------------<wbr>---------------<br>
</div>
<div>Any help on my question is highly appreciated.</div>
<div>Thank you in advance.</div>
<div><br>
<br>
</div>
</div></div></div>
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</blockquote>
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</div>
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</blockquote></div><br></div>