CNN based Compressed Sensing reconstruction has attracted much attention. It is difficult to restore higher spatial frequency components even with CNN-CS. We proposed a new transformed image domain CNN-CS method based on equal-sized multi-resolution image decomposition (eFREBAS transform). The eFREBAS transform is multi resolution analysis method that divide the image into equal-sized sub-images. This CNN consisting of three U-Net CNNs, each with multi-channel input and output reconstructs MR phase varied images in frequency band-to-band through estimating artifact-free sub-images from under-sampled sub-images. Reconstruction experiments showed that eFREBAS-CNN could reconstruct sharp images that have strong phase variation.