regqc feature

autoafids/config/snakebids.yml

@@ -153,6 +153,17 @@ parse_args:
     action: "store_true"  # Automatically sets to True when flag is used
     default: false        # Default to False when not used
 
+  --LEAD-DBS-DIR:
+    help: 'Path to a LEAD-DBS derivatives dataset, for folder(s) that contains multiple derivatives datasets (default: %(default)s) '
+    default: false
+    required: false
+    type: str
+
+  --FMRIPREP-DIR:
+    help: 'Path to a fMRIPrep derivatives dataset, for folder(s) that contains multiple derivatives datasets (default: %(default)s) '
+    default: false
+    required: false
+    type: str
 
   --workdir:
     help: |
@@ -166,10 +177,12 @@ parse_args:
 
 # Nifti template
 templatet1w: 'resources/tpl-MNI152NLin2009cAsym_res-01_T1w.nii.gz'
+templatet1w_lead: 'resources/tpl-MNI152NLin2009bAsym_res-01_T1w.nii.gz'
 
 # AFIDs fcsv template
 fcsv: 'resources/dummy.fcsv'
 fcsv_mni: 'resources/tpl-MNI152NLin2009cAsym_res-01_desc-groundtruth_afids.fcsv'
+fcsv_mni_lead: 'resources/tpl-MNI152NLin2009bAsym_res-01_desc-groundtruth_afids.fcsv'
 
 singularity:
   synthstrip: 'docker://freesurfer/synthstrip:1.3'

autoafids/resources/tpl-MNI152NLin2009bAsym_res-01_desc-groundtruth_afids.fcsv

@@ -0,0 +1,35 @@
+# Markups fiducial file version = 4.6
+# CoordinateSystem = 0
+# columns = id,x,y,z,ow,ox,oy,oz,vis,sel,lock,label,desc,associatedNodeID
+vtkMRMLMarkupsFiducialNode_1,-0.204861407692308,2.72288076923077,-4.88105282051282,0,0,0,1,1,1,0,1,AC,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_2,-0.00726026948717949,-25.0450538461538,-2.21068230769231,0,0,0,1,1,1,0,2,PC,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_3,0.025998141025641,-37.691917948718,-11.0111497435897,0,0,0,1,1,1,0,3,infracollicular sulcus,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_4,-0.0892198512820513,-23.1885743589744,-21.5288358974359,0,0,0,1,1,1,0,4,PMJ,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_5,-0.05649251,-13.7676564102564,-10.950028974359,0,0,0,1,1,1,0,5,superior interpeduncular fossa,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_6,13.3113025641026,-25.951058974359,-9.74885435897436,0,0,0,1,1,1,0,6,R superior LMS,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_7,-13.607458974359,-26.4451,-9.7076082051282,0,0,0,1,1,1,0,7,L superior LMS,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_8,10.8321820512821,-30.8104076923077,-21.5949358974359,0,0,0,1,1,1,0,8,R inferior LMS,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_9,-10.9824102564103,-30.8778025641026,-21.4372025641026,0,0,0,1,1,1,0,9,L inferior LMS,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_10,0.0100564897435897,-52.5094615384615,2.14842435897436,0,0,0,1,1,1,0,10,culmen,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_11,-0.0743417574102564,-8.36030051282051,-15.9354820512821,0,0,0,1,1,1,0,11,intermammillary sulcus,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_12,2.02761256410256,-8.15453153846154,-15.0245538461538,0,0,0,1,1,1,0,12,R MB,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_13,-2.19342487179487,-8.21593282051282,-15.0426743589744,0,0,0,1,1,1,0,13,L MB,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_14,0.00940744421052632,-31.5985789473684,0.568596455263158,0,0,0,1,1,1,0,14,pineal gland,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_15,15.1850526315789,5.61940868421053,24.9488552631579,0,0,0,1,1,1,0,15,R LV at AC,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_16,-15.7984342105263,5.47038342105263,25.0905473684211,0,0,0,1,1,1,0,16,L LV at AC,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_17,18.7231289473684,-22.0626210526316,28.0333394736842,0,0,0,1,1,1,0,17,R LV at PC,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_18,-18.4848157894737,-22.2426736842105,28.1745157894737,0,0,0,1,1,1,0,18,L LV at PC,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_19,-0.111086676315789,33.3615236842105,2.12355523157895,0,0,0,1,1,1,0,19,Genu of CC,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_20,0.116840065,-37.6019447368421,6.49650894736842,0,0,0,1,1,1,0,20,Splenium,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_21,34.0034921052632,-4.056905,-27.3505,0,0,0,1,1,1,0,21,R AL temporal horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_22,-34.8327763157895,-6.646575,-25.3468578947368,0,0,0,1,1,1,0,22,L AL temporal horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_23,17.4263131578947,-10.0524047368421,-18.2650921052632,0,0,0,1,1,1,0,23,R superior AM temporal horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_24,-18.1468184210526,-10.9803721052632,-18.3750131578947,0,0,0,1,1,1,0,24,L superior AM temporal horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_25,20.4641447368421,-4.03479921052632,-28.0214973684211,0,0,0,1,1,1,0,25,R inferior AM temporal horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_26,-21.3443842105263,-5.12460973684211,-27.9912052631579,0,0,0,1,1,1,0,26,L inferior AM temporal horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_27,14.6365184210526,-40.7174131578947,4.71004973684211,0,0,0,1,1,1,0,27,R indusium griseum origin,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_28,-14.8907842105263,-43.0901605263158,4.23491921052632,0,0,0,1,1,1,0,28,L indusium griseum origin,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_29,20.8308868421053,-79.2528368421053,4.51120236842105,0,0,0,1,1,1,0,29,R ventral occipital horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_30,-18.9085052631579,-82.82955,3.54751710526316,0,0,0,1,1,1,0,30,L ventral occipital horn,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_31,11.8931421052632,18.5102315789474,-12.3773210526316,0,0,0,1,1,1,0,31,R olfactory sulcal fundus,vtkMRMLScalarVolumeNode1
+vtkMRMLMarkupsFiducialNode_32,-13.3650815789474,17.0294973684211,-13.0638105263158,0,0,0,1,1,1,0,32,L olfactory sulcal fundus,vtkMRMLScalarVolumeNode1

autoafids/workflow/Snakefile

@@ -346,6 +346,9 @@ if config["fidqc"]:
 
     include: "rules/fidqc.smk"
 
+if config["LEAD_DBS_DIR"] or config["FMRIPREP_DIR"]:
+    print("..... Registration QC Enabled .....")
+    include: "rules/regqc.smk"
 
 rule all:
     input:
@@ -369,6 +372,17 @@ rule all:
         )
         if config["fidqc"]
         else [],
+        regqc=inputs[config["modality"]].expand(
+            bids(
+                root=root,
+                datatype="regqc",
+                desc="reg",
+                suffix="qc.html",
+                **inputs[config["modality"]].wildcards
+            )
+        ) 
+        if config["LEAD_DBS_DIR"] or config["FMRIPREP_DIR"] 
+        else [],
         afidspred=inputs[config["modality"]].expand(
             bids(
                 root=root,

autoafids/workflow/envs/utils.yaml

@@ -1,4 +1,4 @@
 ---
 name: utils
 channels: [conda-forge, defaults]
-dependencies: [python=3.9, nibabel, pandas, matplotlib, joblib]
+dependencies: [python=3.9, nibabel, pandas, matplotlib, joblib, plotly, simpleitk, scipy]

autoafids/workflow/profiles/default/config.yaml

@@ -1,2 +1,2 @@
 use-conda: True
-conda-frontend: conda
+conda-frontend: conda

autoafids/workflow/rules/regqc.smk

@@ -0,0 +1,129 @@
+from pathlib import Path
+import glob
+
+lead_dbs_dir = config.get("LEAD_DBS_DIR", False)
+fmriprep_dir = config.get("FMRIPREP_DIR", False)
+
+def get_warp_path(subject):
+    if lead_dbs_dir:
+        trans_dir = (
+            Path(lead_dbs_dir)
+            / f"sub-{subject}"
+            / "normalization"
+            / "transformations"
+        )
+        pattern = f"sub-{subject}*_from-MNI*_to-anchorNative_desc-ants.nii.gz"
+        matches = list(trans_dir.glob(pattern))
+        if matches:
+            return str(matches[0])
+        return None
+
+    elif fmriprep_dir:
+        trans_dir = (
+            Path(fmriprep_dir)
+            / f"sub-{subject}"
+            / "anat"
+        )
+        pattern = f"sub-{subject}*from-T1w_to-MNI*_mode-image_xfm.h5"
+        matches = list(trans_dir.glob(pattern))
+        if matches:
+            return str(matches[0])
+        return None
+
+    else:
+        raise ValueError("No LEAD-DBS or fMRIPrep directory provided for warp.")
+
+def get_optional_matrix_path(subject):
+    trans_dir = (
+        Path(lead_dbs_dir)
+        / f"sub-{subject}"
+        / "coregistration"
+        / "transformations"
+    )
+    pattern = f"sub-{subject}_desc-precoreg_*T1w.mat"
+    matches = list(trans_dir.glob(pattern))
+    if matches:
+        return str(matches[0])
+    return []
+
+def get_resampled_im(subject):
+    if lead_dbs_dir:
+        pattern = str(
+            Path(lead_dbs_dir)
+            / f"sub-{subject}"
+            / "normalization"
+            / "anat"
+            / f"sub-{subject}_ses-preop_space-*_desc-preproc_acq-*_T1w.nii*"
+        )
+        matches = glob.glob(pattern)
+        if matches:
+            return matches[0]
+        else:
+            raise FileNotFoundError(f"No resampled image found for subject {subject} in LEAD-DBS")
+
+    elif fmriprep_dir:
+        pattern = str(
+            Path(fmriprep_dir)
+            / f"sub-{subject}"
+            / "anat"
+            / f"sub-{subject}*_space-MNI*_desc-preproc_T1w.nii.gz"
+        )
+        matches = glob.glob(pattern)
+        if matches:
+            return matches[0]
+        else:
+            raise FileNotFoundError(f"No resampled image found for subject {subject} in fMRIPrep")
+
+    else:
+        raise ValueError("No LEAD-DBS or fMRIPrep directory provided for resampled image.")
+
+def get_ref_paths():
+    if lead_dbs_dir:
+        refimage = str(Path(workflow.basedir).parent / config["templatet1w_lead"])
+        refcoordinate = str(Path(workflow.basedir).parent / config["fcsv_mni_lead"])
+    else:
+        refimage = str(Path(workflow.basedir).parent / config["templatet1w"])
+        refcoordinate = str(Path(workflow.basedir).parent / config["fcsv_mni"])
+    return refimage, refcoordinate
+
+rule regqc:
+    input:
+        afidfcsv=bids(
+            root=root,
+            datatype="afids-cnn",
+            desc="afidscnn",
+            suffix="afids.fcsv",
+            **inputs[config["modality"]].wildcards
+        ),
+        im=lambda wildcards: get_resampled_im(wildcards.subject),
+        warp=lambda wildcards: get_warp_path(wildcards.subject),
+        optional_matrix=lambda wildcards: get_optional_matrix_path(wildcards.subject),
+    output:
+        html=bids(
+            root=root,
+            datatype="regqc",
+            desc="reg",
+            suffix="qc.html",
+            **inputs[config["modality"]].wildcards
+        ),
+        csv=bids(
+            root=root,
+            datatype="regqc",
+            desc="reg",
+            suffix="qc.csv",
+            **inputs[config["modality"]].wildcards
+        ),
+        fcsv=bids(
+            root=root,
+            datatype="regqc",
+            desc="reg",
+            suffix="afids.fcsv",
+            **inputs[config["modality"]].wildcards
+        ),
+    params:
+        refim=lambda wildcards: get_ref_paths()[0],
+        refcoord=lambda wildcards: get_ref_paths()[1],
+    conda:
+        "../envs/utils.yaml"
+    script:
+        "../scripts/regqc.py"

autoafids/workflow/scripts/apply.py

@@ -377,21 +377,7 @@ def apply_model(
         mni_fid_resampled,
         radius,
     )
-    # do it again to improve prediction
-    fid_pred = np.rint(fid_resampled).astype(int)
-    distances2 = predict_distances(
-        radius,
-        model,
-        fid_pred,
-        img_data,
-    )
-    fid_resampled2 = process_distances(
-        distances2,
-        img_data,
-        fid_pred,
-        radius,
-    )
-    return fid_voxel2world(fid_resampled2, img.affine)
+    return fid_voxel2world(fid_resampled, img.affine)
 
 
 def apply_all(