Nib.load() error - Trying to load PNG and DICOM images to be resized for FCNN

Have 40 DICOM and 40 PNG images (data and their masks) for a Fully CNN that are loaded into my Google Drive and have been found by the notebook via the print(os.listdir(...)), as evidenced below in the first block of code where all the names of the 80 data in the above sets are listed.

Also have globbed all of the DICOM and PNG into img_path and mask_path, both with lengths of 40, in the second block of code that is below.

Now attempting to resize all of the images to 256 x 256 before inputting them into the U-net like architecture for segmentation. However, cannot load them via the nib.load() call, as it cannot work out the file type of the DCM and PNG files, even though for the latter it will not error but still produce an empty set of data like the last block of code yields.

Assuming that, once the first couple of lines inside the for loop in the third block of code are rectified, pre-processing should be completed and I can move onto the U-net implementation.

Have the current pydicom running in the Colab notebook and tried it in lieu of the nib.load() call, which produced the same error as the current one.

---

#import data as data
import pydicom
from PIL import Image
import numpy as np
import glob
import imageio
print(os.listdir("/content/drive/My Drive/Images"))
print(os.listdir("/content/drive/My Drive/Masks"))

pixel_data = []
images = glob.glob("/content/drive/My Drive/Images/IMG*.dcm");
for image in images:
    dataset = pydicom.dcmread(image)
    pixel_data.append(dataset.pixel_array)
#print(len(images))
#print(pixel_data)

pixel_data1 = [] ----------------> this section is the trouble area <-------
masks = glob.glob("content/drive/My Drive/Masks/IMG*.png");
for mask in masks:
    dataset1 = imageio.imread(mask)
    pixel_data1.append(dataset1.pixel_array)
print(len(masks))
print(pixel_data1)

['IMG-0004-00040.dcm', 'IMG-0002-00018.dcm', 'IMG-0046-00034.dcm', 'IMG-0043-00014.dcm', 'IMG-0064-00016.dcm',....] ['IMG-0004-00040.png', 'IMG-0002-00018.png', 'IMG-0046-00034.png', 'IMG-0043-00014.png', 'IMG-0064-00016.png',....]

0 ----------------> outputs of trouble area <--------------

[]

import glob
img_path = glob.glob("/content/drive/My Drive/Images/IMG*.dcm")
mask_path = glob.glob("/content/drive/My Drive/Masks/IMG*.png")
print(len(img_path))
print(len(mask_path))

40

40

images=[]
a=[]
for a in pixel_data:
    a=resize(a,(a.shape[0],256,256))
    a=a[:,:,:]
    for j in range(a.shape[0]):
        images.append((a[j,:,:]))

No output, this section works fine.

images=np.asarray(images)
print(len(images))

10880

masks=[]               -------------------> the other trouble area <-------
b=[]
for b in masks:
    b=resize(b,(b.shape[0],256,256))
    b=b[:,:,:]
    for j in range(b.shape[0]):
        masks.append((b[j,:,:]))

No output, trying to solve the problem of how to fix this section.

masks=np.asarray(masks) ------------> fix the above section and this
print(len(masks))                     should have no issues

[]

You are trying to load the DICOM files again using nib.load, which does not work, as you already found out:

for name in img_path:
    a=nib.load(name)  # does not work with DICOM files
    a=a.get_data()
    a=resize(a,(a.shape[0],256,256))

You already have the data from the DICOM files in the pixel_data list, so you should use these:

for a in pixel_data:
    a=resize(a,(a.shape[0],256,256))  # or something similar, depending on the shape of pixel_data
    ...