Resize a DICOM image in python

Question

I am trying to resize DICOM images of different dimensions into a common dimension size for training my neural network. I thought that cv2 could solve my problem. But I am getting a 'datatype not understood error' in my jupyter notebook

I am trying to create a tensorflow neural network that could predict the class of the image. Thus, I need images of a common dimension size for the first layer training

Here is the function I have created:

IMG_PX_SIZE = 224
def resize(img_dcm):
    return cv2.resize(np.array(img_dcm.pixel_array, (IMG_PX_SIZE,IMG_PX_SIZE)))

This is how I read the dcm files and pass it to the function:

img = pydi.dcmread(PATH)
image = resize(img)

I expected it to output a 224*224 sized image. But I am getting the following error:

<ipython-input-66-3cf283042491> in resize(img_dcm)
      1 IMG_PX_SIZE = 224
      2 def resize(img_dcm):
----> 3     return cv2.resize(np.array(image.pixel_array, (IMG_PX_SIZE,IMG_PX_SIZE)))

TypeError: data type not understood

Answer 1

Here's an alternative way to resize the images using Scikit-Image:

In [105]: from pydicom.data import get_testdata_files

# read a sample image
In [106]: filename = get_testdata_files('MR_small.dcm')[0]
     ...: ds = pydicom.dcmread(filename)

In [107]: data = ds.pixel_array

In [108]: type(data)
Out[108]: numpy.ndarray

In [109]: data.shape
Out[109]: (64, 64)

In [111]: from skimage.transform import resize
In [114]: IMG_PX_SIZE = 32

# resize to new size
In [115]: resized_img = resize(data, (IMG_PX_SIZE, IMG_PX_SIZE), anti_aliasing=True)

In [116]: resized_img.shape
Out[116]: (32, 32)