Segmentation of 3D soft organs from complex volume images is a very important and challenging task. The objects of interest may have inhomogeneous voxel intensities and some object boundaries may be indistinct. Existing algorithms are either sensitive to noise or computationally expensive. This paper presents a novel algorithm that overcomes these shortcomings. The algorithm adopts a novel flipping-free mesh deformation and registration method that can easily incorporate geometric constraints to reduce sensitivity to noise. It efficiently deforms the 3D model in large displacements reducing total computational costs. These properties are confirmed by comprehensive test results.