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ANTsX / ANTs

Advanced Normalization Tools (ANTs)
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--R is ignored during ANTS command line call #881

Closed dorkylever closed 4 years ago

dorkylever commented 4 years ago

Hi Everyone, I am trying to use ANTs to segment a specific part of an embryonic forebrain using uCT scans of whole embryos as MINC volumes. Currently, no mouse atlas exists for uCT data at the stage of development we are investigating.

To achieve this, I rotated the embryo (18288_norm_het_e3_20170810_214322/18288_norm_het_e3_rot.mnc) and manually segmented the region of interest within Display and saved the label as a MINC volume (18288_norm_het_e3_label.mnc).

To test the segmentation, I am trying to register the label to the original unrotated scan (18288_norm_het_e3_20170810_214322/18288_norm_het_e3_20170810_214322_215338.mnc) running the following bash command locally on a subnode of a computing cluster:

ANTS 3 --number-of-affine-iterations 5 --R 201x266x335x200x190x150 -t 'SyN[0.1]' -r 'DMFFD[0,1]' -i 100x100x100x10 -m 'CC[18288_norm_het_e3_20170810_214322/18288_norm_het_e3_rot.mnc,18288_norm_het_e3_20170810_214322/18288_norm_het_e3_20170810_214322_215338.mnc,1, 1,3]' -x 18288_norm_het_e3_label.mnc -o test_ANTS.mnc

but the --R parameter is ignored. [kyle_arkell@compute-5-2 fov5_fb_zic2_het_veh]$ ANTS 3 --number-of-affine-iterations 5 --R 201x266x335x200x190x150 -t 'SyN[0.1]' -r 'DMFFD[0,1]' -i 100x100x100x10 -m 'CC[18288_norm_het_e3_20170810_214322/18288_norm_het_e3_rot.mnc,18288_norm_het_e3_20170810_214322/18288_norm_het_e3_20170810_214322_215338.mnc,1, 1,3]' -x 18288_norm_het_e3_label.mnc -o test_ANTS.mnc

WARNING: Unknown options -R

Run Reg values 1

Running the command without --R is resulting in the entire embryo being labelled even with the mask specified.

At the current time, is an alternative command for sub-field segmentation?

Kind Regards, Kyle Drover

gdevenyi commented 4 years ago 
--R 
TODO/FIXME: the --R sets an ROI option -- it passes a vector of parameters that 
sets the center and bounding box 
of the region of interest for a sub-field 
registration. e.g. in 3D the option setting 
-r 10x12x15x50x50x25 
sets up a 
bounding box of size 50,50,25 with origin at 10,12,15 in voxel (should this be 
physical?) coordinates. 
<VALUES>: 0

Looks like this doesn't work and documented as such. Furthermore, ANTS is deprecated so its unlikely to ever be fixed. Please look into antsRegistration instead.

cookpa commented 4 years ago

ANTS is not much maintained, so it's unlikely the --R option will be fixed (but pull requests are always welcome). However, you can use the -x option with ANTS to set a mask in the fixed space.

cookpa commented 4 years ago

Reading more closely, I am not sure why you want to mask the registration at all. If you know the moving image is only a rotation of the fixed image, why use SyN at all? Would you not be better to just apply a rotation? You can do this with antsRegistration using the option -t Rigid.

You can then apply the resulting rigid transform to your segmentation image with antsApplyTransforms.

dorkylever commented 4 years ago

Hi Everyone,

Thanks @gdevenyi, I didn't realise ANTs was depreceated. I'll give AntsRegistration a go.

@cookpa thanks for the help. I was doing this command as a negative control as I plan to do the same command to label unsegmented scans. I presumed --number-of-affine-iterations did the rotations before the nonlinear transformations.

The -x option with ANTS labels the entire embryo (I think because the intensities are relatively similar in the scan). I've shown the label on the fixed image below:

image

I couldn't show the final output due to server time out but here is the warp:

image

Kind Regards, Kyle Drover

cookpa commented 4 years ago

Sorry @Dorky-Lever I'm not sure what's going on here. antsRegistration might be helpful as it will let you specify masks in either or both the fixed and moving space, and also lets you specify a mask only for the deformable stage. But your mask for your ROI and your mask for the registration will likely be different.

The registration mask tells the program to only compute the registration metrics inside the mask. With your ANTS command it looks like you wanted to set a cuboid of size 200x190x150 voxels. So if you can draw this inside your fixed image, then do something like:

  antsRegistrationSyNQuick.sh -f $fixed -m $moving -t s -x cuboid.nii.gz -o movingToFixed

This will print an example antsRegistration command you can modify. There's also a more detailed registration available with antsRegistrationSyN.sh. You would then call antsApplyTransforms to apply the warps to your forebrain label image.

Note that in ANTS and antsRegistration, the fixed image is the first one in the metric, so your args are -m CC[fixed, moving]. You need to be aware of this when calling antsApplyTransforms to deform your forebrain labels.

https://github.com/ANTsX/ANTs/wiki/Forward-and-inverse-warps-for-warping-images,-pointsets-and-Jacobians

dorkylever commented 4 years ago

Hi Philip, thanks for the help. What directory is $ANTSPATH meant to be directed towards for antsRegistrationSyNQuick.sh?

@gdevenyi I can't find a /bin/ANTS/ or bin/ants/ folder in the MINC-VM and $ANTSPATH is unset.

In the meantime, I've been trying to run an antsRegistration call using the following command that was modified from the example in the wiki but the following mask-less rigid transform:

antsRegistration--dimensionality 3 --float 0 --verbose 1 --minc \ -o [/home/kyle_arkell/fov5_fb_zic2_het_veh/pennTemplateto${sub}_,/home/kyle_arkell/fov5_fb_zic2_het_veh/pennTemplateto${sub}_Warped.mnc] \ --interpolation GenericLabel[interpolator=Linear] \ --winsorize-image-intensities [0.05,0.95] --use-histogram-matching 0 \ --initial-moving-transform [/home/kyle_arkell/fov5_fb_zic2_het_veh/18288_norm_het_e3_20170810_214322/18288_norm_het_e3_rot.mnc,/home/kyle_arkell/fov5_fb_zic2_het_veh/18288_norm_het_e3_20170810_214322/18$ --transform Rigid[0.25] \ --metric MI[/home/kyle_arkell/fov5_fb_zic2_het_veh/18288_norm_het_e3_20170810_214322/18288_norm_het_e3_rot.mnc,/home/kyle_arkell/fov5_fb_zic2_het_veh/18288_norm_het_e3_20170810_214322/18288_norm_hete3$ -c [100x50x25x10,1e-6,10] \ --shrink-factors 8x4x2x1 \ --smoothing-sigmas 3x2x1x0vox

uses > 5600 CPU+ time on a subnode of a computing cluster after stage 0 (just to generate the appropiate MINC files???). This seems to be a lot computing power just to register an identical volume that was rotated by volrot. Is there something that I'm obviously doing wrong? Maybe the wrong -o setting?

gdevenyi commented 4 years ago

If you have questions about MINC-VM open an issue with MINC-VM

gdevenyi commented 4 years ago

--interpolation GenericLabel[interpolator=Linear] is an inappropriate interpolator for a non-label file.

This is where all the CPU time is going.

cookpa commented 4 years ago

Agreed, please see here for examples of how to apply warps. You want to do the registration on the brain images, then warp the label images with antsApplyTransforms. You can use GenericLabel in the apply transforms step, but not in the registration.

https://github.com/ANTsX/ANTs/wiki/Forward-and-inverse-warps-for-warping-images,-pointsets-and-Jacobians

dorkylever commented 4 years ago

Hi everyone,

This was the solution I was able to develop (e3_rot_copy is the fixed image and $file is the moving):

/usr/local/bin/antsRegistration --verbose 1 --dimensionality 3 --float 0 --collapse-output-transforms 0 \ --output [synq,synqWarped.nii.gz,synqInverseWarped.nii.gz] --interpolation Linear \ --use-histogram-matching 0 --winsorize-image-intensities [0.005,0.995] \ --initial-moving-transform [../e3_rot_copy.mnc,$file,1] \ --transform Rigid[0.1] --metric MI[../e3_rot_copy.mnc,$file,1,32,Regular,0.25] \ --convergence [1000x500x250x0,1e-6,10] --shrink-factors 12x8x4x2 --smoothing-sigmas 4x3x2x1vox \ --transform Affine[0.1] --metric MI[../e3_rot_copy.mnc,$file,1,32,Regular,0.25] \ --convergence [1000x500x250x0,1e-6,10] --shrink-factors 12x8x4x2 --smoothing-sigmas 4x3x2x1vox --transform SyN[0.1,3,0] \ --metric CC[../e3_rot_copy.mnc,$file,1,3] --convergence [100x100x70x50x0,1e-6,10] --shrink-factors 10x6x4x2x1 --smoothing-sigmas 5x3x2x1x0vox

antsApplyTransforms -d 3 -i ../forebrainlabel.mnc -r $file -t [synq0DerivedInitialMovingTranslation.mat,1] -t [synq1Rigid.mat,1] -t [synq2Affine.mat,1] -t synq3InverseWarp.nii -o labelled${file}

It still seems to use a lot of CPU time after the SyN registration (stage 2), is -- interpolation Linear similar to GenericLabel when it comes to CPU time? If not, I'll raise a new issue.

Stage 2 iterations = 100x100x70x50x0 convergence threshold = 1.0000e-06 convergence window size = 10 number of levels = 5 using the CC metric (radius = 3, weight = 1.0000e+00) preprocessing: winsorizing the image intensities Shrink factors (level 1 out of 5): [10, 10, 10] Shrink factors (level 2 out of 5): [6, 6, 6] Shrink factors (level 3 out of 5): [4, 4, 4] Shrink factors (level 4 out of 5): [2, 2, 2] Shrink factors (level 5 out of 5): [1, 1, 1] smoothing sigmas per level: [5, 3, 2, 1, 0] Using default NONE metricSamplingStrategy

Running SyN registration (varianceForUpdateField = 3.0000e+00, varianceForTotalField = 0.0000e+00)

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-6.882594948045e-01, 6.449060017878e-06, 1.1652e+02, 1.0152e+00, 1DIAGNOSTIC, 97, -6.884251542803e-01, 6.492445196120e-06, 1.1763e+02, 1.1156e+00, 1DIAGNOSTIC, 98, -6.883261728083e-01, 5.983517125172e-06, 1.1877e+02, 1.1325e+00, 1DIAGNOSTIC, 99, -6.885658852606e-01, 6.156359856121e-06, 1.1986e+02, 1.0903e+00, 1DIAGNOSTIC, 100, -6.885244787803e-01, 5.698477046961e-06, 1.2089e+02, 1.0384e+00, XXDIAGNOSTIC,Iteration,metricValue,convergenceValue,ITERATION_TIME_INDEX,SINCE_LAST 1DIAGNOSTIC, 1, -5.478174321200e-01, 1.797693134862e+308, 1.3373e+02, 1.2834e+01, 1DIAGNOSTIC, 2, -5.501428774450e-01, 1.797693134862e+308, 1.3580e+02, 2.0708e+00, 1DIAGNOSTIC, 3, -5.525788883084e-01, 1.797693134862e+308, 1.3797e+02, 2.1681e+00, 1DIAGNOSTIC, 4, -5.548264014744e-01, 1.797693134862e+308, 1.4006e+02, 2.0973e+00, 1DIAGNOSTIC, 5, -5.568047634982e-01, 1.797693134862e+308, 1.4217e+02, 2.1037e+00, 1DIAGNOSTIC, 6, -5.584891516358e-01, 1.797693134862e+308, 1.4421e+02, 2.0392e+00, 1DIAGNOSTIC, 7, -5.599689107365e-01, 1.797693134862e+308, 1.4637e+02, 2.1615e+00, 1DIAGNOSTIC, 8, -5.614159196040e-01, 1.797693134862e+308, 1.4848e+02, 2.1091e+00, 1DIAGNOSTIC, 9, -5.623971229704e-01, 1.797693134862e+308, 1.5077e+02, 2.2931e+00, 1DIAGNOSTIC, 10, -5.633532704958e-01, 1.796145213321e-03, 1.5299e+02, 2.2230e+00, 1DIAGNOSTIC, 11, -5.641476105151e-01, 1.445743868999e-03, 1.5524e+02, 2.2475e+00, 1DIAGNOSTIC, 12, -5.648283170573e-01, 1.150819682287e-03, 1.5751e+02, 2.2721e+00, 1DIAGNOSTIC, 13, -5.654633750799e-01, 9.167132571159e-04, 1.5982e+02, 2.3084e+00, 1DIAGNOSTIC, 14, -5.660794674018e-01, 7.361100746961e-04, 1.6211e+02, 2.2851e+00, 1DIAGNOSTIC, 15, -5.666330536738e-01, 5.976452483401e-04, 1.6443e+02, 2.3252e+00, 1DIAGNOSTIC, 16, -5.670786413880e-01, 4.888065770658e-04, 1.6671e+02, 2.2732e+00, 1DIAGNOSTIC, 17, -5.675389538052e-01, 4.051787064311e-04, 1.6899e+02, 2.2865e+00, 1DIAGNOSTIC, 18, -5.679033947619e-01, 3.441898151452e-04, 1.7124e+02, 2.2432e+00, 1DIAGNOSTIC, 19, -5.682621146892e-01, 2.931709176645e-04, 1.7353e+02, 2.2981e+00, 1DIAGNOSTIC, 20, -5.686136327964e-01, 2.529167352939e-04, 1.7579e+02, 2.2536e+00, 1DIAGNOSTIC, 21, -5.689475853025e-01, 2.199942892372e-04, 1.7806e+02, 2.2778e+00, 1DIAGNOSTIC, 22, -5.691811474482e-01, 1.904354508639e-04, 1.8038e+02, 2.3156e+00, 1DIAGNOSTIC, 23, -5.694897693438e-01, 1.663079439109e-04, 1.8273e+02, 2.3501e+00, 1DIAGNOSTIC, 24, -5.697454697854e-01, 1.468396200014e-04, 1.8498e+02, 2.2493e+00, 1DIAGNOSTIC, 25, -5.700079404058e-01, 1.315646462940e-04, 1.8725e+02, 2.2726e+00, 1DIAGNOSTIC, 26, -5.702159986887e-01, 1.177106260316e-04, 1.8956e+02, 2.3030e+00, 1DIAGNOSTIC, 27, -5.704610549418e-01, 1.069960750264e-04, 1.9192e+02, 2.3609e+00, 1DIAGNOSTIC, 28, -5.706555409642e-01, 9.699561535691e-05, 1.9421e+02, 2.2906e+00, 1DIAGNOSTIC, 29, -5.708601292971e-01, 8.828914606469e-05, 1.9641e+02, 2.2039e+00, 1DIAGNOSTIC, 30, -5.710313846378e-01, 8.057776396517e-05, 1.9871e+02, 2.3037e+00, 1DIAGNOSTIC, 31, -5.712088131664e-01, 7.409106368152e-05, 2.0108e+02, 2.3639e+00, 1DIAGNOSTIC, 32, -5.714073451209e-01, 6.777971623043e-05, 2.0337e+02, 2.2911e+00, 1DIAGNOSTIC, 33, -5.715142521373e-01, 6.175692096146e-05, 2.0572e+02, 2.3500e+00, 1DIAGNOSTIC, 34, -5.716400609680e-01, 5.591091382819e-05, 2.0772e+02, 2.0013e+00, 1DIAGNOSTIC, 35, -5.718317497065e-01, 5.165585559633e-05, 2.0999e+02, 2.2658e+00, 1DIAGNOSTIC, 36, -5.719225028469e-01, 4.687526964756e-05, 2.1241e+02, 2.4217e+00, 1DIAGNOSTIC, 37, -5.721121909668e-01, 4.384176623775e-05, 2.1453e+02, 2.1225e+00, 1DIAGNOSTIC, 38, -5.721672129712e-01, 4.010694692114e-05, 2.1652e+02, 1.9927e+00, 1DIAGNOSTIC, 39, -5.723440635375e-01, 3.772651062883e-05, 2.1853e+02, 2.0031e+00, 1DIAGNOSTIC, 40, -5.723749451936e-01, 3.440484873085e-05, 2.2050e+02, 1.9762e+00, 1DIAGNOSTIC, 41, -5.725408369431e-01, 3.220316377136e-05, 2.2260e+02, 2.1014e+00, 1DIAGNOSTIC, 42, -5.726217257546e-01, 3.040116590849e-05, 2.2471e+02, 2.1091e+00, 1DIAGNOSTIC, 43, -5.726931825645e-01, 2.791044350468e-05, 2.2625e+02, 1.5378e+00, 1DIAGNOSTIC, 44, -5.727989104895e-01, 2.554212600847e-05, 2.2828e+02, 2.0330e+00, 1DIAGNOSTIC, 45, -5.728960640092e-01, 2.410157061430e-05, 2.3029e+02, 2.0087e+00, 1DIAGNOSTIC, 46, -5.729860595941e-01, 2.239634455918e-05, 2.3231e+02, 2.0140e+00, 1DIAGNOSTIC, 47, -5.731116224892e-01, 2.203847884426e-05, 2.3438e+02, 2.0778e+00, 1DIAGNOSTIC, 48, -5.731425596113e-01, 2.049739484703e-05, 2.3650e+02, 2.1186e+00, 1DIAGNOSTIC, 49, -5.732774771700e-01, 2.032798117602e-05, 2.3837e+02, 1.8634e+00, 1DIAGNOSTIC, 50, -5.732809403826e-01, 1.855953035499e-05, 2.4050e+02, 2.1291e+00, 1DIAGNOSTIC, 51, -5.734164843102e-01, 1.810116628857e-05, 2.4253e+02, 2.0381e+00, 1DIAGNOSTIC, 52, -5.734436714275e-01, 1.699228200251e-05, 2.4458e+02, 2.0435e+00, 1DIAGNOSTIC, 53, -5.735129405247e-01, 1.567374072416e-05, 2.4661e+02, 2.0333e+00, 1DIAGNOSTIC, 54, -5.735822564602e-01, 1.456594963125e-05, 2.4871e+02, 2.1018e+00, 1DIAGNOSTIC, 55, -5.736740510927e-01, 1.385432737878e-05, 2.5068e+02, 1.9725e+00, 1DIAGNOSTIC, 56, -5.736834778751e-01, 1.274508049156e-05, 2.5268e+02, 1.9961e+00, 1DIAGNOSTIC, 57, -5.737260792583e-01, 1.199425924822e-05, 2.5494e+02, 2.2605e+00, 1DIAGNOSTIC, 58, -5.738437466590e-01, 1.142799969420e-05, 2.5716e+02, 2.2167e+00, 1DIAGNOSTIC, 59, -5.738558313130e-01, 1.105993360270e-05, 2.5940e+02, 2.2426e+00, 1DIAGNOSTIC, 60, -5.739350876712e-01, 1.036104083688e-05, 2.6166e+02, 2.2639e+00, 1DIAGNOSTIC, 61, -5.739757830142e-01, 1.018638132412e-05, 2.6391e+02, 2.2487e+00, 1DIAGNOSTIC, 62, -5.740130240227e-01, 9.600104029200e-06, 2.6619e+02, 2.2723e+00, 1DIAGNOSTIC, 63, -5.740745973260e-01, 9.178484387438e-06, 2.6845e+02, 2.2677e+00, 1DIAGNOSTIC, 64, -5.741735301308e-01, 9.221945842849e-06, 2.7067e+02, 2.2155e+00, 1DIAGNOSTIC, 65, -5.741398524045e-01, 8.864305967769e-06, 2.7290e+02, 2.2304e+00, 1DIAGNOSTIC, 66, -5.742929765017e-01, 8.959488429050e-06, 2.7515e+02, 2.2499e+00, 1DIAGNOSTIC, 67, -5.742747816576e-01, 8.371744697564e-06, 2.7735e+02, 2.2046e+00, 1DIAGNOSTIC, 68, -5.743247349915e-01, 8.282707380503e-06, 2.7963e+02, 2.2724e+00, 1DIAGNOSTIC, 69, -5.743486229435e-01, 7.688454382910e-06, 2.8188e+02, 2.2521e+00, 1DIAGNOSTIC, 70, -5.744464984937e-01, 7.674465805366e-06, 2.8416e+02, 2.2802e+00, 1DIAGNOSTIC, 71, -5.744377337780e-01, 7.169838395913e-06, 2.8639e+02, 2.2342e+00, 1DIAGNOSTIC, 72, -5.745044310356e-01, 6.753372078633e-06, 2.8866e+02, 2.2628e+00, 1DIAGNOSTIC, 73, -5.745323958600e-01, 6.338012467848e-06, 2.9090e+02, 2.2404e+00, 1DIAGNOSTIC, 74, -5.745599511576e-01, 6.227100651526e-06, 2.9316e+02, 2.2622e+00, 1DIAGNOSTIC, 75, -5.746177957439e-01, 5.688414462579e-06, 2.9540e+02, 2.2391e+00, 1DIAGNOSTIC, 76, -5.746614186275e-01, 5.948541610217e-06, 2.9766e+02, 2.2663e+00, 1DIAGNOSTIC, 77, -5.746961725215e-01, 5.770103461752e-06, 2.9990e+02, 2.2359e+00, 1DIAGNOSTIC, 78, -5.747056337207e-01, 5.459208284717e-06, 3.0212e+02, 2.2191e+00, 1DIAGNOSTIC, 79, -5.748127217377e-01, 5.484276750026e-06, 3.0444e+02, 2.3265e+00, 1DIAGNOSTIC, 80, -5.747636343728e-01, 5.309115206902e-06, 3.0667e+02, 2.2288e+00, 1DIAGNOSTIC, 81, -5.748396318294e-01, 5.081835090499e-06, 3.0889e+02, 2.2178e+00, 1DIAGNOSTIC, 82, -5.748794120411e-01, 5.046529692996e-06, 3.1113e+02, 2.2354e+00, 1DIAGNOSTIC, 83, -5.748983404720e-01, 4.837214792462e-06, 3.1338e+02, 2.2543e+00, 1DIAGNOSTIC, 84, -5.749534911488e-01, 4.687212202143e-06, 3.1557e+02, 2.1936e+00, 1DIAGNOSTIC, 85, -5.749458566143e-01, 4.411693033916e-06, 3.1786e+02, 2.2830e+00, 1DIAGNOSTIC, 86, -5.750188779817e-01, 4.433052574805e-06, 3.2018e+02, 2.3267e+00, 1DIAGNOSTIC, 87, -5.750681423901e-01, 4.530497020875e-06, 3.2241e+02, 2.2290e+00, 1DIAGNOSTIC, 88, -5.750954382532e-01, 4.410080084094e-06, 3.2468e+02, 2.2626e+00, 1DIAGNOSTIC, 89, -5.751252725828e-01, 4.684237185599e-06, 3.2701e+02, 2.3307e+00, 1DIAGNOSTIC, 90, -5.751433094272e-01, 4.354083887206e-06, 3.2922e+02, 2.2096e+00, 1DIAGNOSTIC, 91, -5.751807558125e-01, 4.259256114804e-06, 3.3146e+02, 2.2395e+00, 1DIAGNOSTIC, 92, -5.752137983900e-01, 4.174146985723e-06, 3.3362e+02, 2.1655e+00, 1DIAGNOSTIC, 93, -5.752424591715e-01, 3.967797700498e-06, 3.3588e+02, 2.2565e+00, 1DIAGNOSTIC, 94, -5.752303680401e-01, 3.650861654879e-06, 3.3815e+02, 2.2675e+00, 1DIAGNOSTIC, 95, -5.752860449165e-01, 3.270068794707e-06, 3.4038e+02, 2.2365e+00, 1DIAGNOSTIC, 96, -5.752708335648e-01, 2.899238941393e-06, 3.4263e+02, 2.2487e+00, 1DIAGNOSTIC, 97, -5.753486265873e-01, 2.939635845411e-06, 3.4477e+02, 2.1403e+00, 1DIAGNOSTIC, 98, -5.753593142269e-01, 2.908900333101e-06, 3.4689e+02, 2.1148e+00, 1DIAGNOSTIC, 99, -5.754309956893e-01, 3.142863580316e-06, 3.4901e+02, 2.1268e+00, 1DIAGNOSTIC, 100, -5.754048582665e-01, 3.050384876153e-06, 3.5099e+02, 1.9761e+00, XXDIAGNOSTIC,Iteration,metricValue,convergenceValue,ITERATION_TIME_INDEX,SINCE_LAST 1DIAGNOSTIC, 1, -4.941563324304e-01, 1.797693134862e+308, 3.6635e+02, 1.5364e+01, 1DIAGNOSTIC, 2, -4.954949842679e-01, 1.797693134862e+308, 3.7017e+02, 3.8130e+00, 1DIAGNOSTIC, 3, -4.969231430088e-01, 1.797693134862e+308, 3.7455e+02, 4.3867e+00, 1DIAGNOSTIC, 4, -4.984845149246e-01, 1.797693134862e+308, 3.7886e+02, 4.3119e+00, 1DIAGNOSTIC, 5, -4.998981729679e-01, 1.797693134862e+308, 3.8365e+02, 4.7838e+00, 1DIAGNOSTIC, 6, -5.012013732835e-01, 1.797693134862e+308, 3.8842e+02, 4.7766e+00, 1DIAGNOSTIC, 7, -5.022688717718e-01, 1.797693134862e+308, 3.9318e+02, 4.7579e+00, 1DIAGNOSTIC, 8, -5.033516286720e-01, 1.797693134862e+308, 3.9790e+02, 4.7178e+00, 1DIAGNOSTIC, 9, -5.042059056685e-01, 1.797693134862e+308, 4.0246e+02, 4.5639e+00, 1DIAGNOSTIC, 10, -5.048673554966e-01, 1.413562215848e-03, 4.0725e+02, 4.7835e+00, 1DIAGNOSTIC, 11, -5.054441078314e-01, 1.174304102570e-03, 4.1229e+02, 5.0400e+00, 1DIAGNOSTIC, 12, -5.059944008132e-01, 9.585675453345e-04, 4.1703e+02, 4.7459e+00, 1DIAGNOSTIC, 13, -5.064695689680e-01, 7.717066931921e-04, 4.2185e+02, 4.8139e+00, 1DIAGNOSTIC, 14, 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4.504180233581e-05, 2.1168e+03, 2.9566e+01, ^[[A^[[A^[[A Elapsed time (stage 2): 2140

Total elapsed time: 2276

antsRegistation is still running when observed with top

Kind Regards Kyle Drover

cookpa commented 4 years ago

It has to compose and write the warps as well as the output image itself. It may take some time if your images are large.

cookpa commented 4 years ago

Closing for now

dorkylever commented 4 years ago

Hi Phillip and Gabriel,

Sorry its been a while but I was able to get AntsRegistration working for our uCT scans of 12.5 embryos. I had to modify the code returned from QuickSyns.sh to use CC instead of MI for embryos scans as they were too few overlapping voxels between scans.

My current solution is available at: https://github.com/Dorky-Lever/Ark_Vol_Warper_v1

Depending on whether my collected results are significant after whole embryo volume normalisation, our lab may be able to publish these results and code. You guys at least deserve acknowledgements and I'll keep you updated.

Kind Regards, Kyle Drover

cookpa commented 4 years ago

It's pretty unusual for MI to have insufficient overlap at the deformable stage, assuming the affine has worked reasonably well. If you call antsApplyTransforms without the deformation field, you can see how the affine alignment worked, ie

antsApplyTransforms -d 3 -i ../forebrain_label.mnc -r $file -t [synq0DerivedInitialMovingTranslation.mat,1] -t [synq1Rigid.mat,1] -t [synq2Affine.mat,1] -o labelled_${file}

I'm assuming here that forebrain_label.mnc is in the same space as e3_rot_copy.mnc. If this is a label image and you want label output, you would add -n GenericLabel (for accuracy) or -n NearestNeighbor (for speed) to the antsApplyTransforms call.

Since you have turned collapse-transforms off, you can also work backwards up the chain of transforms, to assess how well each one worked.

dorkylever commented 4 years ago

Hi Phillip,

Thanks for the help. The affine transformations don't work well for these scans but that is expected. The uCT scans aren't full body and have artifacts caused by our uCT scanning protocol.

I've checked the warped labels visually using Display and the current code seems to be pretty accurate for our use (the SyN transformation takes around 1 hour). Would -n GenericLabel significantly increase computational time (I have nearly finished processing ~140 different scans with three different labels)?

Kind Regards, Kyle Drover

cookpa commented 4 years ago

As long as you are saving the warps, you can apply the transforms later with different interpolation, without re-doing the registration. The default interpolation is linear. If you're calling antsApplyTransforms multiple times to warp independent binary labels, it's easy enough to threshold them later. But if you have three labels in one image, you probably don't want linear interpolation.

I'm a bit concerned that the affine registration is so far off as to result in insufficient overlap for MI. Deformable registration without good affine initialization can lead to overfitting. But I am not familiar at all with your data.