Cannot feed image data of DICOM into image data generator

Şiyar Bahadır :

So i have preprocessed some dicom images to feed a neural network, and in image augmentation step, the image data generator expects a 4d input while my data is 3d (200, 420, 420)

i tried reshaping the array and expanding dimensions, but in both cases i cannot plot the individual images in the array (expects image with shape 420, 420 and instead my new images have shape 420, 420, 1)

and here are my codes;

I have three functions to convert DICOM images into images with good contrast;

This one takes housefield units

def transform_to_hu(medical_image, image):
    intercept = medical_image.RescaleIntercept
    slope = medical_image.RescaleSlope
    hu_image = image * slope + intercept

    return hu_image

This one sets window image values;

def window_image(image, window_center, window_width):
    img_min = window_center - window_width // 2
    img_max = window_center + window_width // 2
    window_image = image.copy()
    window_image[window_image < img_min] = img_min
    window_image[window_image > img_max] = img_max

    return window_image

And this function loads the image:

def load_image(file_path):
    medical_image = dicom.read_file(file_path)
    image = medical_image.pixel_array

    hu_image = transform_to_hu(medical_image, image)
    brain_image = window_image(hu_image, 40, 80)
    return brain_image

Then i load my images:

files = sorted(glob.glob('F:\CT_Data_Classifier\*.dcm'))
images = np.array([load_image(path) for path in files])

images.shape returns (200, 512, 512) and everything is fine about the data, for example i can plot 100th image by plt.imshow(images[100]) and it plots an image

i then feed the data into image data generator

train_image_data = ImageDataGenerator(
    rescale=1./255,
    shear_range=0.,
    zoom_range=0.05,
    rotation_range=180,
    width_shift_range=0.05,
    height_shift_range=0.05,
    horizontal_flip=True,
    vertical_flip=True,
    fill_mode='constant',
    cval=0

but then, when i try to plot, with this code:

plt.figure(figsize=(12, 12))
for X_batch, y_batch in train_image_data.flow(trainX, trainY, batch_size=9):
    for i in range(0, 9):
        plt.subplot(330 + 1 + i)
        plt.imshow(X_batch[i])
    plt.show()
    break 

it returns

(ValueError: ('Input data in "NumpyArrayIterator" should have rank 4. You passed an array with shape', (162, 420, 420)))

i tried expand_dims and reshape to add an extra dimension at the end of the array to represent channels but then it returns

TypeError: Invalid shape (420, 420, 1) for image data

in the plt.imshow stage

im a doctor and not an experienced programmer, so i would really appreciate your help. cheers.

jakub :

You are correct in adding an extra dimension to represent channels. That part seems fine. The problem is with plotting. For that, you can use:

plt.matshow(x[..., 0]).

where x is the 3D array. The syntax x[..., 0] means take index 0 of the last dimension of array x. The ellipsis (...) is shorthand to fill in the dimensions. For a 3D array, the equivalent call would be x[:, :, 0].