ROI (region of interest) plays an important role in medical image analysis. In this paper, an efficient approach to ROI extraction based on monotonically marching curve evolution is proposed. The improvement is in two aspects: first, a new monotonically marching snake integrating ROI information is presented by minimizing the new defined ROI energy. Due to the region based speed term, the front could even propagate in low contrast and narrow thin areas. Second, a multi-initial fast marching algorithm is developed for numerical implementation, where a multi-initial scheme can perform the selective growth of the front, thus further reduce the front leaking. Furthermore, a multiscale scheme for numerical implementation is adopted, where a fast passing solution method is used for determining the initial solution on the finer scale that greatly reduces the computational cost. The validity of the proposed approach is demonstrated on the medical image ROI extraction. Experimental results show that the approach is efficient both in computational cost and segmentation quality. Low contrast and narrow thin ROI could be efficiently extracted precisely by the approach.