No matlab

.gitmodules

@@ -1,3 +0,0 @@
-[submodule "hippunfold/hippocampal_autotop"]
-	path = hippunfold/hippocampal_autotop
-	url = http://github.com/jordandekraker/hippocampal_autotop

Dockerfile

@@ -1,4 +1,4 @@
-FROM khanlab/autotop_deps:v0.3.1
+FROM khanlab/autotop_deps:v0.4.0
 
 MAINTAINER [email protected]
 

MANIFEST.in

@@ -1,8 +1,3 @@
 recursive-include hippunfold/resources *
 recursive-include hippunfold/config *
 recursive-include hippunfold/workflow *
-recursive-include hippunfold/hippocampal_autotop/tools *
-recursive-include hippunfold/hippocampal_autotop/mcr_v97 *
-recursive-include hippunfold/hippocampal_autotop/misc *
-recursive-include hippunfold/hippocampal_autotop/atlases *
-recursive-include hippunfold/hippocampal_autotop/CNNmodels *

hippunfold/config/snakebids.yml

@@ -155,6 +155,13 @@ parse_args:
     default: False
     action: 'store_true'
 
+  --skip_inject_template_labels:
+    help: 'Set this flag to skip post-processing template injection into CNN segmentation (default: %(default)s)'
+    default: False
+    action: 'store_true'
+
+
+
   --rigid_reg_template:
     help: 'Use rigid instead of affine for registration to template. Try this if your images are reduced FOV (default: %(default)s)'
     default: False
@@ -180,8 +187,8 @@ parse_args:
     help: 'Sets the output space for results (default: %(default)s)'
 
 
-  --archive_work:
-    help: 'Archive work folder for each subject after completion, saving space/files (default: %(default)s)'
+  --keep_work:
+    help: 'Keep work folder intact instead of archiving it for each subject (default: %(default)s)'
     default: False
     action: 'store_true'
 
@@ -190,7 +197,7 @@ parse_args:
 
 singularity:
   prepdwi: 'docker://khanlab/prepdwi:latest'  
-  autotop: 'docker://khanlab/autotop_deps:v0.2'
+  autotop: 'docker://khanlab/autotop_deps:v0.4.0'
   fsl: '/project/6050199/akhanf/singularity/bids-apps/fsl_6.0.3_cuda9.1.sif'  #fsl with cuda container not on docker hub yet.. only used for dwi workflow anyhow..
   ants: 'docker://kaczmarj/ants:2.3.4'
 
@@ -200,9 +207,9 @@ template: CITI168
 
 template_files:
   CITI168:
-    T1w: hippocampal_autotop/atlases/CITI/CIT168_T1w_head_700um.nii.gz
-    xfm_corobl: hippocampal_autotop/atlases/CITI/CoronalOblique_rigid.txt
-    crop_ref: hippocampal_autotop/atlases/CITI/img_300umCoronalOblique_hemi-{hemi}.nii.gz
+    T1w: resources/CITI168/T1w_head_700um.nii.gz
+    xfm_corobl: resources/CITI168/CoronalOblique_rigid.txt
+    crop_ref: resources/CITI168/T2w_300umCoronalOblique_hemi-{hemi}.nii.gz
 
 
 rigid_reg_template: False
@@ -244,6 +251,60 @@ hippdwi_opts:
     L: '224 351'
   bbox_y: '198 453'
 
+unfold_vol_ref:
+  dims:
+    - '256'
+    - '128'
+    - '16'
+  voxdims:
+    - '0.15625'
+    - '0.15625'
+    - '0.15625'
+  origin:
+    - '0'
+    - '200'
+    - '0'
+  orient: RPI
+
+shape_inject:
+  labels_reg: 
+    - 1
+    - 2
+    - 3
+    - 4
+    - 5
+    - 6
+  labels_reinsert:
+    - 7
+  label_smoothing_stdev: '0.5x0.5x0.5mm'
+
+laplace_labels:
+  AP: 
+    gm:
+      - 1
+      - 8
+    src:
+      - 5
+    sink:
+      - 6
+  PD:
+    gm:
+      - 1
+      - 8
+    src:
+      - 3
+    sink:
+      - 8   
+  IO:
+    gm:
+      - 1
+      - 8
+    src:
+      - 2
+      - 4
+      - 7
+    sink:
+      - 0 
 
 #---- dwi options below, not used in the default workflow ----
 
@@ -275,4 +336,4 @@ masking:
     #'0015': 'bet_from-b0_frac-4'
     '0015': 'b0SyN_from-MNI152NLin2009cSym'
 
-
+archive_work: False

hippunfold/resources/CITI168/CoronalOblique_rigid.txt

@@ -0,0 +1,5 @@
+#Insight Transform File V1.0
+#Transform 0
+Transform: MatrixOffsetTransformBase_double_3_3
+Parameters: 1 0 0 0 0.809017 -0.587785 0 0.587785 0.809017 -6.10623e-16 4.36795 -9.04318
+FixedParameters: 0 0 0

hippunfold/resources/tpl-upenn/.gitignore

@@ -0,0 +1 @@
+.snakemake

hippunfold/resources/tpl-upenn/Snakefile

@@ -0,0 +1,80 @@
+configfile: '../../config/snakebids.yml'
+
+wildcard_constraints:
+    i = '[0-9]+'
+
+
+
+rule all:
+    input: expand('tpl-upenn_dir-{dir}_level-0_coords.nii.gz', dir=['AP','PD','IO'])
+
+rule create_PD_sink:
+    """ this rule is still a WIP and shouldn't be used.. """
+    input:
+        lbl = 'tpl-upenn_desc-hipptissue_dseg.nii.gz',
+    output:
+        lbl = 'tpl-upenn_desc-withPDsink_level-0_dseg.nii.gz',
+    container: config['singularity']['autotop']
+    shell:
+        # dilate DG into the SRLM (lbl 2/4/7) and background (lbl 0) to get a PD sink that is outside the laplace domain
+        #  create a new label for each region dilated into, so the AP/IO src/sink are unaffected
+        #    we can do this easily by just adding 10 to the existing labels (0 -> 10, 2 -> 12, 4->14, 7->17
+        'c3d {input} -retain-labels 8 -dilate 8 1x1x1vox -binarize -popas DILATED_DG ' 
+        ' {input} -replace 0 10 -retain-labels 2 4 7 10 -binarize -push DILATED_DG -multiply -as DG_SINK '
+        ' -scale 10 {input} -add -o {output}' # add 10 to original labels, and save it
+
+rule downsample_coords:
+    input: 
+        lbl = lambda wildcards: 'tpl-upenn_desc-withPDsink_level-{i}_dseg.nii.gz'.format(i=int(wildcards.i)-1)
+    output:
+        lbl = 'tpl-upenn_desc-withPDsink_level-{i}_dseg.nii.gz',
+    shell:
+        'c3d {input} -interpolation NearestNeighbor -resample 50%  {output}'
+
+
+# run laplace coords without initialization only for lowest resolution
+#  this is done by setting constraint on output i  (i.e. {i,2})
+rule laplace_coords:
+    input:
+        lbl = 'tpl-upenn_desc-withPDsink_level-{i}_dseg.nii.gz',
+    params:
+        gm_labels = lambda wildcards: config['laplace_labels'][wildcards.dir]['gm'],
+        src_labels = lambda wildcards: config['laplace_labels'][wildcards.dir]['src'],
+        sink_labels = lambda wildcards: config['laplace_labels'][wildcards.dir]['sink'],
+        convergence_threshold = 1e-6,
+        max_iters = 100000
+    output:
+        coords = 'tpl-upenn_dir-{dir}_level-{i,2}_coords.nii.gz'
+    resources:
+        time = 1200
+    log: 'log_dir-{dir}_level-{i}_laplace.txt'
+    script: '../../workflow/scripts/laplace_coords.py'
+
+
+rule laplace_init_lores:
+    input:
+        lbl = 'tpl-upenn_desc-withPDsink_level-{i}_dseg.nii.gz',
+        init_coords = 'tpl-upenn_dir-{dir}_level-{i}_desc-upsampled_coords.nii.gz'
+    params:
+        gm_labels = lambda wildcards: config['laplace_labels'][wildcards.dir]['gm'],
+        src_labels = lambda wildcards: config['laplace_labels'][wildcards.dir]['src'],
+        sink_labels = lambda wildcards: config['laplace_labels'][wildcards.dir]['sink'],
+        convergence_threshold = 1e-8,
+        max_iters = 100000
+    output:
+        coords = 'tpl-upenn_dir-{dir}_level-{i,0|1}_coords.nii.gz'
+    resources:
+        time = 1200
+    log: 'log_dir-{dir}_level-{i}_laplace.txt'
+    script: '../../workflow/scripts/laplace_coords_withinit.py'
+
+
+rule upsample_coords:
+    input:
+        coords = lambda wildcards: 'tpl-upenn_dir-{dir}_level-{i}_coords.nii.gz'.format(dir=wildcards.dir, i=int(wildcards.i)+1)
+    output:
+        coords = 'tpl-upenn_dir-{dir}_level-{i}_desc-upsampled_coords.nii.gz'
+    shell:
+        'c3d {input} -interpolation NearestNeighbor -resample 200%  {output}'
+
+