Accurate geometrical reconstruction of human bones into three-dimensional(3D) view is currently required for clinical studies such as enabling the radiologists to well analyze the fractures or infections in the bones, evidence of arthritis, presence of dental decays, lung infections etc. CT-scan is commonly used to obtain accurate reconstruction of the human body. However, this method is quite relucent for the patients as it demands a large number of image data sets, typically, more than 100s of images for a single bone to reconstruct. Analysis using MRI are also meant especially to investigate the anatomy and physiology of the body in both health and disease. However, although quite accurate, CTscan is not an appropriate 3D reconstruction method because of the high irradiating dose, high price and large input data volume. Thus, a 3D model reconstructed from 2D X-ray images can be a useful alternative. The generation of the 3D model is termed as 3D reconstruction from 2D X-Ray images. The reconstruction of the X-ray images can be achieved from both single and multiple X-Ray images. Many researches have been carried out in this field and the reconstruction has been carried out with varying accuracy. This paper presents a review of the existing methods for accurate 3D reconstruction from bi-planar X-rays. General Terms3D Reconstruction, X-Ray images.

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The problem for optimal team formation is an important issue for many software organizations especially for small and medium size organization because of the experience of employee, constraints and skill requirements for a particular project are neither is supported by database system nor it is possible for small and medium scale organization due to bit complex issue for them . More over success or failure of software product is mostly depends on the development team. Mostly people uses their managerial experience to form software development team, but always it cannot meet the optimal decision specially when time and cost are the main constraints and of employee pool is having mixed kind of expertise. For that scenario in this paper our aim was to develop a selection model combining analytical hierarchy process (AHP) and Bayesian network for choosing the efficient developers. Additionally, that it is also defining the optimum order among developers based on their capability and also quantities among selected developers based on sensitivity values. The proposed model is based on expert's judgments and the human error is inevitable. Therefore, the robust design of quality developer selection is to be investigated. General TermsMulti-criteria decision making.