We present a general phase regularized image reconstruction method that is robust to phase wraps in initial solutions, with application to partial Fourier imaging, chemical shift imaging and flow imaging. The problem of constraining phase structures in reconstruction was studied under a regularized inverse problem framework. Since phase regularized reconstruction is inherently non-convex and sensitive to phase wraps in the initial solution, a reconstruction technique, named phase cycling, was proposed. The proposed method was applied to in vivo datasets and compared with state of the art reconstruction methods. The proposed phase cycling reconstruction provides an alternative way to perform phase regularized reconstruction, without the need of performing phase unwraping. It is robust to the choice of initial solutions and flexible to incorporate into different phase imaging applications.