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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)