diff --git a/stanford_pipeline/utils/count_axons.py b/stanford_pipeline/utils/count_axons.py
new file mode 100644
index 0000000..7317832
--- /dev/null
+++ b/stanford_pipeline/utils/count_axons.py
@@ -0,0 +1,46 @@
+'''Reads myelinated + unmyelinated axon morphometric files and count axons.
+'''
+from pathlib import Path
+from tqdm import tqdm
+import argparse
+import pandas as pd
+
+def main():
+    parser = argparse.ArgumentParser(description='Aggregate morphometrics.')
+    parser.add_argument('input_dir', type=str, help='Path to the folder containing all morphometric files.')
+    parser.add_argument('output_name', type=str, help='Name of the output file.')
+
+    args = parser.parse_args()
+    input_dir = Path(args.input_dir)
+    out_name = args.output_name
+    assert input_dir.exists(), f'Directory {input_dir} does not exist.'
+
+    # find images except for the masks
+    mask_suffixes = (
+        '_seg-axon.png', '_seg-myelin.png', '_seg-uaxon.png', '_uaxon_index.png', 
+        '_seg-axonmyelin.png', '_axonmyelin_index.png', '_index.png',
+    )
+    inputs = [f for f in input_dir.glob('*.png') if not f.name.endswith(mask_suffixes)]
+
+    counts = {'image': [], 'axon_count': [], 'uaxon_count': []}
+    axon_morph_suffix = '_axon_morphometrics.xlsx'
+    uaxon_morph_suffix = '_uaxon_morphometrics.xlsx'
+
+    for img in tqdm(inputs):
+        # read morphometric files
+        axon_count = len(pd.read_excel(str(img.with_suffix('')) + axon_morph_suffix))
+        uaxon_count = len(pd.read_excel(str(img.with_suffix('')) + uaxon_morph_suffix))
+
+        # add data
+        counts['image'].append(img.stem)
+        counts['axon_count'].append(axon_count)
+        counts['uaxon_count'].append(uaxon_count)
+
+    # save counts
+    df = pd.DataFrame(counts)
+    df.to_csv(out_name, index=False)
+
+
+    
+if __name__ == "__main__":
+    main()
\ No newline at end of file
diff --git a/stanford_pipeline/utils/extract_axon_masks.py b/stanford_pipeline/utils/extract_axon_masks.py
index 569e199..c1cbd0f 100644
--- a/stanford_pipeline/utils/extract_axon_masks.py
+++ b/stanford_pipeline/utils/extract_axon_masks.py
@@ -1,3 +1,7 @@
+'''Extracts axon and myelin masks from nnunet raw predictions. This util writes 
+binary masks for axon, myelin and unmyelinated axon classes. The axon and myelin
+masks are also merged.
+'''
 import cv2
 import argparse
 import numpy as np