Sphinx Recon_surf and CerebNet API's

CerebNet/apply_warp.py

@@ -14,20 +14,52 @@
 # limitations under the License.
 
 # IMPORTS
-from os.path import join
 import numpy as np
 import nibabel as nib
 
+from os.path import join
 from CerebNet.datasets import utils
 
 
 def save_nii_image(img_data, save_path, header, affine):
+    """
+    Save an image data array as a NIfTI file.
+
+    Parameters
+    ----------
+    img_data : ndarray
+        The image data to be saved.
+    save_path : str
+        The path (including file name) where the image will be saved.
+    header : nibabel.Nifti1Header
+        The header information for the NIfTI file.
+    affine : ndarray
+        The affine matrix for the NIfTI file.
+    """
+
     img_out = nib.Nifti1Image(img_data, header=header, affine=affine)
     print(f"Saving {save_path}")
     nib.save(img_out, save_path)
 
 
-def store_warped_data(img_path, lbl_path, warp_path, result_path, patch_size):
+def main(img_path, lbl_path, warp_path, result_path, patch_size):
+
+    """
+    Load, warp, crop, and save both an image and its corresponding label based on a given warp field.
+
+    Parameters
+    ----------
+    img_path : str
+        Path to the T1-weighted MRI image to be warped.
+    lbl_path : str
+        Path to the label image corresponding to the T1 image, to be warped similarly.
+    warp_path : str
+        Path to the warp field file used to warp the images.
+    result_path : str
+        Directory path where the warped and cropped images will be saved.
+    patch_size : tuple of int
+        The dimensions (height, width, depth) cropped images after warping.
+    """
 
     img, img_file = utils.load_reorient_rescale_image(img_path)
 
@@ -78,7 +110,7 @@ def store_warped_data(img_path, lbl_path, warp_path, result_path, patch_size):
 
     args = parser.parse_args()
     warp_path = join(args.result_path, args.warp_filename)
-    store_warped_data(args.img_path,
+    main(args.img_path,
                       args.lbl_path,
                       warp_path=warp_path,
                       result_path=args.result_path,

CerebNet/inference.py

@@ -14,17 +14,16 @@
 
 # IMPORTS
 import time
+import nibabel as nib
+import numpy as np
+import torch
+
 from os import makedirs
 from os.path import join, dirname, isfile
 from typing import Dict, List, Tuple, Optional
 from concurrent.futures import Future, ThreadPoolExecutor
-
-import nibabel as nib
-import numpy as np
-import torch
 from torch.utils.data import DataLoader
 from tqdm import tqdm
-
 from FastSurferCNN.utils import logging
 from FastSurferCNN.utils.threads import get_num_threads
 from FastSurferCNN.utils.mapper import JsonColorLookupTable, TSVLookupTable
@@ -44,6 +43,9 @@
 
 
 class Inference:
+    """
+    Manages inference operations, including batch processing, data loading, and model predictions for neuroimaging data.
+    """
     def __init__(
         self,
         cfg: "yacs.ConfigNode",

CerebNet/run_prediction.py

@@ -30,6 +30,14 @@
 
 
 def setup_options():
+    """
+    Configure and return an argument parser for the segmentation script.
+
+    Returns
+    -------
+    argparse.ArgumentParser
+        The configured argument parser.
+    """
     # Training settings
     parser = argparse.ArgumentParser(description="Segmentation")
 
@@ -94,6 +102,28 @@ def setup_options():
 
 
 def main(args):
+    """
+    Main function to run the inference based on the given command line arguments.
+    This implementation is inspired by methods described in CerebNet for cerebellum sub-segmentation.
+
+    Parameters
+    ----------
+    args : argparse.Namespace
+        Command line arguments parsed by `argparse.ArgumentParser`.
+
+    Returns
+    -------
+    int 
+        Returns 0 upon successful execution to indicate success.
+    str
+        A message indicating the failure reason in case of an exception.
+
+    References
+    ----------
+    Faber J, Kuegler D, Bahrami E, et al. CerebNet: A fast and reliable deep-learning 
+    pipeline for detailed cerebellum sub-segmentation. NeuroImage 264 (2022), 119703. 
+    https://doi.org/10.1016/j.neuroimage.2022.119703
+    """
     cfg = get_config(args)
     cfg.TEST.ENABLE = True
     cfg.TRAIN.ENABLE = False

doc/api/index.rst

@@ -9,4 +9,4 @@ FastSurfer API
     FastSurferCNN.utils.rst
     FastSurferCNN.data_loader.rst
     recon_surf.rst
-
+    CerebNet.rst

doc/api/recon_surf.rst

@@ -10,6 +10,17 @@ API recon_surf References
     align_points
     align_seg
     create_annotation
+    fs_balabels
+    lta
+    map_surf_label
+    N4_bias_correct
+    paint_cc_into_pred
+    rewrite_mc_surface
+    rotate_sphere
+    sample_parc
+    smooth_aparc
+    spherically_project_wrapper
+
 
 
 

doc/conf.py

@@ -21,10 +21,6 @@
 import os
 sys.path.append(os.path.dirname(__file__) + '/..') 
 sys.path.append(os.path.dirname(__file__) + '/../recon_surf') 
-# sys.path.insert(0, '..') #after
-
-# autodoc_mock_imports = ["torch", "yacs"]
-
 
 project = 'FastSurfer'
 copyright = '2023, Martin Reuter'