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Dear Freesurfer expert
I have found this problem when I am running infant freesurfer on newborn mri
image.
Best regards
Knut Jørgen Bjuland
mri_convert --conform
/home/knutjb/subjects/EPOP510_fs/work/mprage.nu.conf.nii.gz
/home/knutjb/subjects/EPOP510_fs/work/sscnn/conformed.nii.gz
WARNING
==================++++++++++++++++++++++++=======================================
The physical sizes are (316.00 mm, 316.00 mm, 316.00 mm), which cannot fit in
256^3 mm^3 volume.
The resulting volume will have 316 slices.
If you find problems, please let us know (freesurfer@nmr.mgh.harvard.edu).
==================================================++++++++++++++++++++++++===============
reading from /home/knutjb/subjects/EPOP510_fs/work/mprage.nu.conf.nii.gz...
TR=2400.00, TE=0.00, TI=0.00, flip angle=0.00
i_ras = (-0.998888, 0.0471505, 5.29093e-11)
j_ras = (-0.0107408, -0.227545, -0.973708)
k_ras = (0.0459108, 0.972625, -0.227799)
Reslicing using trilinear interpolation
writing to /home/knutjb/subjects/EPOP510_fs/work/sscnn/conformed.nii.gz...
[<tf.Tensor 'bnorm_D_1_00_1/cond/Merge:0' shape=(?, 256, 256, 32)
dtype=float32>, <tf.Tensor 'bnorm_D_1_01_1/cond/Merge:0' shape=(?, 256, 256,
32) dtype=float32>, <tf.Tensor 'bnorm_D_1_10_1/cond/Merge:0' shape=(?, 128,
128, 64) dtype=float32>, <tf.Tensor 'bnorm_D_1_11_1/cond/Merge:0' shape=(?,
128, 128, 64) dtype=float32>, <tf.Tensor 'bnorm_D_1_20_1/cond/Merge:0'
shape=(?, 64, 64, 128) dtype=float32>, <tf.Tensor 'bnorm_D_1_21_1/cond/Merge:0'
shape=(?, 64, 64, 128) dtype=float32>, <tf.Tensor 'bnorm_D_1_30_1/cond/Merge:0'
shape=(?, 32, 32, 256) dtype=float32>, <tf.Tensor 'bnorm_D_1_31_1/cond/Merge:0'
shape=(?, 32, 32, 256) dtype=float32>, <tf.Tensor 'bnorm_D_1_40_1/cond/Merge:0'
shape=(?, 16, 16, 512) dtype=float32>, <tf.Tensor 'bnorm_D_1_41_1/cond/Merge:0'
shape=(?, 16, 16, 512) dtype=float32>, <tf.Tensor 'bnorm_D_1_50_1/cond/Merge:0'
shape=(?, 8, 8, 1024) dtype=float32>, <tf.Tensor 'bnorm_D_1_51_1/cond/Merge:0'
shape=(?, 8, 8, 1024) dtype=float32>]
12
Loaded model file:
/usr/local/infantsfreesurfer/average/sscnn_skullstripping/cor_sscnn.h5
2.073170731707317
Image max is :2.0650406504065044
Traceback (most recent call last):
File "/usr/local/infantsfreesurfer/python/scripts/sscnn_skullstrip", line 74,
in <module>
cor_img_data = predict('cor')
File "/usr/local/infantsfreesurfer/python/scripts/sscnn_skullstrip", line 70,
in predict
net.predict_slice_segmentation([conformed_file], [args.contrast],
direction_fullnames[direction], out_membership_file, out_hard_file)
File
"/usr/local/infantsfreesurfer/python/packages/sscnn_skullstripping/deeplearn_utils/DeepImageSynth.py",
line 807, in predict_slice_segmentation
out_slices = self.model.predict(input_feature_array)
File
"/usr/local/infantsfreesurfer/python/lib/python3.6/site-packages/keras/engine/training.py",
line 1147, in predict
x, _, _ = self._standardize_user_data(x)
File
"/usr/local/infantsfreesurfer/python/lib/python3.6/site-packages/keras/engine/training.py",
line 749, in _standardize_user_data
exception_prefix='input')
File
"/usr/local/infantsfreesurfer/python/lib/python3.6/site-packages/keras/engine/training_utils.py",
line 137, in standardize_input_data
str(data_shape))
ValueError: Error when checking input: expected input_ax to have shape (256,
256, 1) but got array with shape (316, 316, 1)
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