Can you please solve this question using MATLAB ?

I need the code please.

Exercise 2: The data file slice6_32coils.mat contains actual raw complex k-space data for one 1.5 mm thick slice (out of total of 35 slices) of an object imaged with the MRI machine. The data files contain 32 individual 1024 x 522 k-space data matrices, each obtained from a different receiver coil. Each of these k-space data matrices can be used to reconstruct an imperfect and partial MRI image Biomedical Engineering 1. Reconstruct the 32 coils images via discrete two-dimensional Fourier transform. Display the gray scale images from coil 1,7,13,19,25 and 31 in one figure. Comment on how the images are different. Useful functions: imshow, subplot, mat2 gray, abs Hint: Recall the MATLAB functions fftshift and ifftshift to position the image correctly. 2. You should now have 32 reconstructed partial images of the object. To produce the final complete image, try combining the coil images by (1) averaging and (ii) the sum of squares (S.S) reconstruction. Let zo stand for the pixel value at (x,y) of the ith coil image. In the SoS reconstruction, these values are combined as Sos (290() 3. Compute the signal-to-noise ratio in the final SOS-reconstructed image Compare it to the signal-to-noise ratio in the individual coil reconstructed images. Use the same coils as in 1. For signal containing region, use two Region of Interests (ROI 1 and ROI 2), the ROI I with limits in x and y as [650:690 260:290), ROI 2 with limits as [490:530 130:170). For noise containing region, use [1:40 1:40] as x and y limits. Comment on results. (3 pts) Exercise 2: The data file slice6_32coils.mat contains actual raw complex k-space data for one 1.5 mm thick slice (out of total of 35 slices) of an object imaged with the MRI machine. The data files contain 32 individual 1024 x 522 k-space data matrices, each obtained from a different receiver coil. Each of these k-space data matrices can be used to reconstruct an imperfect and partial MRI image Biomedical Engineering 1. Reconstruct the 32 coils images via discrete two-dimensional Fourier transform. Display the gray scale images from coil 1,7,13,19,25 and 31 in one figure. Comment on how the images are different. Useful functions: imshow, subplot, mat2 gray, abs Hint: Recall the MATLAB functions fftshift and ifftshift to position the image correctly. 2. You should now have 32 reconstructed partial images of the object. To produce the final complete image, try combining the coil images by (1) averaging and (ii) the sum of squares (S.S) reconstruction. Let zo stand for the pixel value at (x,y) of the ith coil image. In the SoS reconstruction, these values are combined as Sos (290() 3. Compute the signal-to-noise ratio in the final SOS-reconstructed image Compare it to the signal-to-noise ratio in the individual coil reconstructed images. Use the same coils as in 1. For signal containing region, use two Region of Interests (ROI 1 and ROI 2), the ROI I with limits in x and y as [650:690 260:290), ROI 2 with limits as [490:530 130:170). For noise containing region, use [1:40 1:40] as x and y limits. Comment on results. (3 pts)