diff --git a/Project.toml b/Project.toml
index 06ae21a..78b3ca8 100644
--- a/Project.toml
+++ b/Project.toml
@@ -39,7 +39,7 @@ Documenter = "1"
 DocumenterVitepress = "0.0.19, 0.0.20"
 HDF5 = "0.17.2"
 Interpolations = "0.15.1"
-ITKIOWrapper = "0.0.2"
+ITKIOWrapper = "0.0.3"
 JLD = "0.13.5"
 JSON = "0.21.4"
 Parameters = "0.12.3"
diff --git a/src/Load_and_save.jl b/src/Load_and_save.jl
index 5d1d979..f4bd53e 100644
--- a/src/Load_and_save.jl
+++ b/src/Load_and_save.jl
@@ -71,7 +71,7 @@ function load_images(path::String, modality::String)::Array{MedImage}
 
     voxel_arr = ITKIOWrapper.loadVoxelData(path,spatial_meta)
     voxel_arr = voxel_arr.dat
-    voxel_arr = permutedims(voxel_arr, (3, 2, 1))
+    voxel_arr = permutedims(voxel_arr, (1, 2, 3))
     spatial_metadata_keys = ["origin", "spacing", "direction"]
     spatial_metadata_values = [origin, spacing, direction]
     spatial_metadata = Dictionaries.Dictionary(spatial_metadata_keys, spatial_metadata_values)
@@ -88,7 +88,7 @@ function create_nii_from_medimage(med_image::MedImage, file_path::String)
   # Convert voxel_data to a numpy array (Assuming voxel_data is stored in Julia array format)
   voxel_data_np = med_image.voxel_data
   voxel_data_np = permutedims(voxel_data_np, (3, 2, 1))
-  # Create a SimpleITK image from numpy array
+   #Create a SimpleITK image from numpy array
   sitk = pyimport("SimpleITK")
   image_sitk = sitk.GetImageFromArray(voxel_data_np)