TransformationImageProcessing.py

# Author: Keshava Prasad Gubbi
# For any questions: Contact keshav.prasad.gubbi@gmail.com

# Script to perform General Image processing on General Image processing on both nrrd and tiff files after downloadng
# from cluster


# DONE: Check which file is it and then pass it onto respective read function that processes it.
# DONE: Basic functions ---> convert to 8 bit, enhance contrast, save file into respective format.
# DONE: Preserve and rewrite the processed nrrd files with rest of the metadata same as the original file.
# TODO: Rewrite the file also as a tiff file with same metadata.

import os
import nrrd
import cv2 as cv

outpath = r'C:/Users/keshavgubbi/Desktop/nifti/standard_output/'
inpath = r'C:/Users/keshavgubbi/Desktop/nifti/standard/'


def read_nrrd_file(f):
    nrrd_image, head = nrrd.read(os.path.join(inpath, f), index_order='F')
    width, height, depth = nrrd_image.shape
    print(f' The image {file} has dimensions :({width}, {height}) with {depth} '
          f'slices')
    datatype = head['type']
    print(f'The Image has dtype: {datatype}. Converting into a int8 (8 bit) image!')
    ce_image = contrast_enhancement(nrrd_image)
    return ce_image.astype('uint8'), head


def image_to_nrrd(image, header):
    return nrrd.write(os.path.join(outpath, f"{name}.nrrd"), image, header=header)


def contrast_enhancement(f):
    alpha = 3.0  # Contrast control (1.0-3.0) but 3 is required for my purposes here
    beta = 1  # Brightness control (0-100). Not to be added beyond 5, to not hamper the signal with salt and pepper
    # noise.
    contrast_enhanced_image = cv.convertScaleAbs(f, alpha=alpha, beta=beta)
    return contrast_enhanced_image


for file in os.listdir(inpath):
    if file.endswith('.nrrd'):
        print(f'Working with Image: {file}')
        # Read the nrrd file and convert it into a 8-bit numpy array after contrast enhancement
        nrrd_image_array, Header = read_nrrd_file(file)
        # print(header)
        name, ext = file.split('.', 1)
        processed_image = image_to_nrrd(nrrd_image_array, Header)
        print(f'####End of processing {file}!##################')