BACKGROUND Three-dimensional (3D) bone shapes need to be created for visualization and pre-operative surgery planning. Conventionally such shape data is extracted from volumetric data sets, obtained by three-dimensional sensors, such as computerized tomography (CT) and magnetic resonance imaging (MRI). This conventional method is highly labor intensive and time consuming. METHODS This paper presents a cost- and time-effective computational method for generating a 3D bone shape from multiple X-ray images. Starting with a predefined 3D template bone shape that is clinically normal and scaled to an average size, our method scales and deforms the template shape until the deformed shape gives an image similar to an input X-ray image when projected onto a two-dimensional (2D) plane. The hierarchical freeform deformation method is used to scale and deform the template bone. The problem of finding the 3D shape of the bond is reduced to a sequence of optimization problems. The objective of this optimization is to minimize the error between the input X-ray image and the projected image of the deformed template shape. The sequential quadratic programming (SQP) is used to solve this multi-dimentional optimization problem. RESULTS The proposed X-ray image-based shape reconstruction is more computationally efficient, cost-effective and portable compared to the conventional CT- or MRI-based methods. Within a couple of minutes with a standard personal computer, the proposed method generates a 3D bone shape that is sufficiently accurate for many applications, such as (a) making a 3D physical mock-up for training and (b) importing into, and using in, a computer-aided planning system for orthopedic surgery, including bone distraction and open/closed wedge osteotomy. CONCLUSIONS Because the proposed method requires only a small number of X-ray images and a minimum input from the user, the method can serve as a cost- and time-effective 3D bone shape reconstruction method for various medical applications.