diff --git a/modules/util/hdf5_conversion.py b/modules/util/hdf5_conversion.py
index 0aa0eb33bd77c252fd2dd24919462d965d175589..60b5617abdbb668858826a930479f7878071a948 100644
--- a/modules/util/hdf5_conversion.py
+++ b/modules/util/hdf5_conversion.py
@@ -3,7 +3,7 @@ import numpy as np
 import pandas as pd
 
 
-def hdf5_to_npz_csv(hdf5_filename, output_file_prefix, chunk_size=1000):
+def hdf5_to_npz_csv(hdf5_filename, output_file_prefix, chunk_size=10000):
     """
     Convert HDF5 files to NumPy's NPZ and CSV formats in chunks.
     Only values where the boolean mask is True are included.
@@ -16,10 +16,10 @@ def hdf5_to_npz_csv(hdf5_filename, output_file_prefix, chunk_size=1000):
 
     # Step 1: Open HDF5 file
     with h5py.File(hdf5_filename, "r") as file:
-        mask = np.asarray(file["mask"])  # If mask needs to be applied, load it into memory
+        mask = np.asarray(file["FOV_mask"])  # If mask needs to be applied, load it into memory
 
         # For each dataset
-        for dataset_name in file.keys():
+        for dataset_name in filter(lambda key: key != "FOV_mask", file.keys()):
             dataset = file[dataset_name]
 
             # Determine how many chunks are needed (rounded up)