From 10dabacf1da9702640e355ad0c1fdd79ba227c92 Mon Sep 17 00:00:00 2001
From: Julien Cohen-Adad <jcohen@polymtl.ca>
Date: Tue, 16 Jan 2024 22:35:51 -0500
Subject: [PATCH] Use manual seg and labeling (#62)

Fixes #54, Fixes #60
---
 data_processing.ipynb | 37 +++++++++++++++++++++++--------------
 1 file changed, 23 insertions(+), 14 deletions(-)

diff --git a/data_processing.ipynb b/data_processing.ipynb
index a8a1939..c466d3c 100644
--- a/data_processing.ipynb
+++ b/data_processing.ipynb
@@ -93,6 +93,7 @@
     "from scipy.interpolate import interp1d\n",
     "from scipy.ndimage import uniform_filter1d\n",
     "from scipy.stats import f_oneway\n",
+    "import shutil\n",
     "from statsmodels.stats.multicomp import pairwise_tukeyhsd"
    ]
   },
@@ -170,6 +171,7 @@
     "\n",
     "path_data = os.getcwd()\n",
     "print(f\"path_data: {path_data}\")\n",
+    "path_labels = os.path.join(path_data, \"derivatives\", \"labels\")\n",
     "path_qc = os.path.join(path_data, \"qc\")\n",
     "shim_modes = [\"CP\", \"patient\", \"volume\", \"phase\", \"CoV\", \"target\", \"SAReff\"]\n",
     "shim_modes_MPRAGE = [\"CP\", \"CoV\"]  # TODO: change variable name PEP8\n",
@@ -198,18 +200,30 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Run segmentation on CoV_T1w scan\n",
+    "# Run segmentation on CoV_T1w scan, unless it is already in the derivatives/labels\n",
     "\n",
     "for subject in subjects:\n",
     "    os.chdir(os.path.join(path_data, subject, \"anat\"))\n",
-    "    !sct_deepseg_sc -i {subject}_acq-CoV_T1w.nii.gz -c t1 -qc {path_qc}"
+    "    fname_manual_seg = os.path.join(path_labels, subject, \"anat\", f\"{subject}_acq-CoV_T1w_seg.nii.gz\")\n",
+    "    if os.path.exists(fname_manual_seg):\n",
+    "        # Manual segmentation already exists. Copy it to local folder\n",
+    "        print(f\"{subject}: Manual segmentation found\\n\")\n",
+    "        shutil.copyfile(fname_manual_seg, f\"{subject}_acq-CoV_T1w_seg.nii.gz\")\n",
+    "        # Generate QC report to make sure the manual segmentation is correct\n",
+    "        !sct_qc -i {subject}_acq-CoV_T1w.nii.gz -s {subject}_acq-CoV_T1w_seg.nii.gz -p sct_deepseg_sc -qc {path_qc} -qc-subject {subject}\n",
+    "    else:\n",
+    "        # Manual segmentation does not exist. Run automatic segmentation.\n",
+    "        print(f\"{subject}: Manual segmentation not found\")\n",
+    "        !sct_deepseg_sc -i {subject}_acq-CoV_T1w.nii.gz -c t1 -qc {path_qc}"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "id": "663bb98c",
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
     "# Crop the images for faster processing\n",
@@ -229,19 +243,14 @@
    "source": [
     "# Vertebral labeling on the CoV_T1w scan\n",
     "\n",
+    "# Given the low resolution of the GRE scan, the automatic detection of C2-C3 disc is unreliable. Therefore, we \n",
+    "# need to use the manual disc labels that are part of the dataset.\n",
     "for subject in subjects:\n",
     "    os.chdir(os.path.join(path_data, subject, \"anat\"))\n",
-    "    !sct_label_vertebrae -i {subject}_acq-CoV_T1w_crop.nii.gz -s {subject}_acq-CoV_T1w_crop_seg.nii.gz -c t1 -qc {path_qc}\n",
-    "    \n",
-    "# TODO: replace by code below\n",
-    "# https://github.com/shimming-toolbox/rf-shimming-7t/issues/59\n",
-    "# Given the low resolution of the GRE scan, the automatic detection of C2-C3 disc is unreliable. Therefore we need to use the manual disc labels that are part of the dataset.\n",
-    "# for subject in subjects:\n",
-    "#     os.chdir(os.path.join(path_data, subject, \"anat\"))\n",
-    "#     fname_label_discs = os.path.join(path_data, \"derivatives\", \"labels\", subject, \"anat\", f\"{subject}_acq-CoV_T2starw_label-discs_dseg.nii.gz\")\n",
-    "#     !sct_label_utils -i {subject}_acq-CoV_T2starw_crop_seg.nii.gz -disc {fname_label_discs} -o {subject}_acq-CoV_T2starw_crop_seg_labeled.nii.gz\n",
-    "#     # Generate QC report to assess labeled segmentation\n",
-    "#     !sct_qc -i {subject}_acq-CoV_T2starw_crop.nii.gz -s {subject}_acq-CoV_T2starw_crop_seg_labeled.nii.gz -p sct_label_vertebrae -qc {path_qc} -qc-subject {subject}"
+    "    fname_label_discs = os.path.join(path_labels, subject, \"anat\", f\"{subject}_acq-CoV_T1w_label-discs_dseg.nii.gz\")\n",
+    "    !sct_label_utils -i {subject}_acq-CoV_T1w_crop_seg.nii.gz -disc {fname_label_discs} -o {subject}_acq-CoV_T1w_crop_seg_labeled.nii.gz\n",
+    "    # Generate QC report to assess labeled segmentation\n",
+    "    !sct_qc -i {subject}_acq-CoV_T1w_crop.nii.gz -s {subject}_acq-CoV_T1w_crop_seg_labeled.nii.gz -p sct_label_vertebrae -qc {path_qc} -qc-subject {subject}"
    ]
   },
   {