diff --git a/Analysis.ipynb b/Analysis.ipynb
index cf36ad1..d82786e 100644
--- a/Analysis.ipynb
+++ b/Analysis.ipynb
@@ -11,23 +11,43 @@
     "\n",
     "The data can be download at: XXX (TODO: upload on openneuro)\n",
     "\n",
-    "The structure of the input dataset is as follows:\n",
+    "The structure of the input dataset is as follows (JSON sidecars are not listed for clarity):\n",
     "~~~\n",
-    "RF_shimming_project_cleanupload/\n",
-    "├── SubA\n",
-    "│   ├── GRE_B1\n",
-    "│   │   ├── CVred\n",
-    "│   │   ├── Noshim\n",
-    "│   │   ├── PatSpec\n",
-    "│   │   ├── PhaseOnly\n",
-    "│   │   ├── SAReff\n",
-    "│   │   ├── Target\n",
-    "│   │   └── VolSpec\n",
-    "│   └── MPRAGE\n",
-    "├── SubB\n",
-    "├── SubC\n",
-    "├── SubD\n",
-    "└── SubE\n",
+    "├── CHANGES\n",
+    "├── README\n",
+    "├── dataset_description.json\n",
+    "├── participants.json\n",
+    "├── participants.tsv\n",
+    "├── sub-01\n",
+    "│   ├── anat\n",
+    "│   │   ├── sub-01_acq-CP_T1w.nii.gz\n",
+    "│   │   ├── sub-01_acq-CP_T2starw.nii.gz\n",
+    "│   │   ├── sub-01_acq-CoV_T1w.nii.gz\n",
+    "│   │   ├── sub-01_acq-CoV_T2starw.nii.gz\n",
+    "│   │   ├── sub-01_acq-SAReff_T2starw.nii.gz\n",
+    "│   │   ├── sub-01_acq-patient_T2starw.nii.gz\n",
+    "│   │   ├── sub-01_acq-phase_T2starw.nii.gz\n",
+    "│   │   ├── sub-01_acq-target_T2starw.nii.gz\n",
+    "│   │   ├── sub-01_acq-volume_T2starw.nii.gz\n",
+    "│   └── fmap\n",
+    "│       ├── sub-01_acq-anatCP_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-anatCoV_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-anatSAReff_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-anatpatient_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-anatphase_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-anattarget_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-anatvolume_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-fampCP_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-fampCoV_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-fampSAReff_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-famppatient_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-fampphase_TB1TFL.nii.gz\n",
+    "│       ├── sub-01_acq-famptarget_TB1TFL.nii.gz\n",
+    "│       └── sub-01_acq-fampvolume_TB1TFL.nii.gz\n",
+    "├── sub-02\n",
+    "├── sub-03\n",
+    "├── sub-04\n",
+    "└── sub-05\n",
     "~~~\n",
     "\n",
     "\n",
@@ -78,9 +98,22 @@
     "!datalad install https://github.com/OpenNeuroDatasets/ds004906.git\n",
     "os.chdir(\"ds004906\")\n",
     "# !datalad get . # uncomment for production\n",
-    "!datalad get sub-01/  # comment for debugging\n",
+    "!datalad get sub-01/  # comment for debugging"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6fe120e8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define useful variables\n",
+    "\n",
     "path_data = os.getcwd()\n",
-    "path_qc = os.path.join(path_data, \"qc\")"
+    "path_qc = os.path.join(path_data, \"qc\")\n",
+    "shim_modes = [\"CP\", \"CoV\", \"patient\", \"phase\", \"SAReff\", \"target\", \"volume\"]\n",
+    "subjects = glob.glob(\"sub-*\")"
    ]
   },
   {
@@ -92,7 +125,6 @@
    "source": [
     "# Run segmentation on GRE scan\n",
     "\n",
-    "subjects = glob.glob(\"sub-*\")\n",
     "for subject in subjects:\n",
     "    os.chdir(os.path.join(path_data, subject, \"anat\"))\n",
     "    !sct_deepseg_sc -i {subject}_acq-CoV_T2starw.nii.gz -c t2 -qc {path_qc}"
@@ -100,7 +132,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "49c57187",
+   "id": "aac9d889",
    "metadata": {},
    "source": [
     "## Verify quality control (QC) report\n",
@@ -111,7 +143,22 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1809bb43",
+   "id": "90deb5e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Crop GRE scan for faster processing and better registration results\n",
+    "\n",
+    "for subject in subjects:\n",
+    "    os.chdir(os.path.join(path_data, subject, \"anat\"))\n",
+    "    !sct_crop_image -i {subject}_acq-CoV_T2starw.nii.gz -m {subject}_acq-CoV_T2starw_seg.nii.gz -dilate 20x20x0 -o {subject}_acq-CoV_T2starw_crop.nii.gz\n",
+    "    !sct_crop_image -i {subject}_acq-CoV_T2starw_seg.nii.gz -m {subject}_acq-CoV_T2starw_seg.nii.gz -dilate 20x20x0 -o {subject}_acq-CoV_T2starw_crop_seg.nii.gz"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e0cde907",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -119,7 +166,8 @@
     "\n",
     "for subject in subjects:\n",
     "    os.chdir(os.path.join(path_data, subject, \"fmap\"))\n",
-    "    !sct_register_multimodal -i {subject}_acq-anatCoV_TB1TFL.nii.gz -d ../anat/{subject}_acq-CoV_T2starw.nii.gz -param step=1,type=im,algo=slicereg,metric=CC -qc {path_qc}"
+    "    for shim_mode in shim_modes:\n",
+    "        !sct_register_multimodal -i {subject}_acq-anat{shim_mode}_TB1TFL.nii.gz -d ../anat/{subject}_acq-CoV_T2starw_crop.nii.gz -dseg ../anat/{subject}_acq-CoV_T2starw_crop_seg.nii.gz -param step=1,type=im,algo=slicereg,metric=CC -qc {path_qc}"
    ]
   }
  ],