| import numpy as np | |
| def complex_to_two_channel_image(complex_img: np.ndarray) -> np.ndarray: | |
| """Converts a complex valued image to a 2 channel image (real and imaginary channels)""" | |
| real, imag = np.real(complex_img), np.imag(complex_img) | |
| return np.concatenate((real, imag), axis=0) | |
| def two_channel_to_complex_image(two_ch_img: np.ndarray) -> np.ndarray: | |
| """Converts a 2 channel image (real and imaginary channels) to a complex valued image""" | |
| two_ch_img = two_ch_img[0] | |
| real = two_ch_img[0] | |
| imag = two_ch_img[1] | |
| complex_image = real + 1j*imag | |
| return complex_image[None,...] | |
| def normalize_complex_coil_image(complex_coil_img: np.ndarray) -> np.ndarray: | |
| """Scales the complex valued coil image """ | |
| max_val = np.percentile(np.abs(complex_coil_img), 99.5) | |
| return complex_coil_img / max_val | |
| def create_three_channel_image(complex_coil_img: np.ndarray) -> np.ndarray: | |
| """Converts a complex valued coil image to a 3 channel image (magnitude channels repated 3 times)""" | |
| mag = np.abs(complex_coil_img) | |
| return np.concatenate((mag, mag, mag), axis=0) | |