Design and Implementation of an Intelligent Photogrammetric System for Control and Guidance of Reconstructive Surgery

The digital image contains efficient and useful information which enables measurement and data acquisition. One of the methods that facilitate measuring and interpreting objects, using the image solely, is close-range photogrammetry. Among the various fields of science, whenever a precise measurement is required, this approach can be applied. One of these fields is Medical Sciences that due to high speed and accuracy of close-range photogrammetry, it can create three-dimensional models. To generate the model there is no need for direct contact with the patients consequently there are no side effects. So in this respect, it is better than other conventional methods in medical imaging which are often invasive procedures. This branch of photogrammetry is known as medical photogrammetry. In this paper, application of intelligent close range photogrammetry in control and guide of reconstructive surgeries is presented. The proposed method is evaluated in a case study of the human face using facial recognition algorithms in two-dimensional space and matching in three-dimensional space. The main objective of this research is to design a system by integrating close-range photogrammetry and intelligent algorithms to guide and control reconstructive surgeries using two-dimensional images and three-dimensional models. The output is geometrical parameters and the changes of input face to transform to the proposed face that surgery is done on part in question at the discretion of the physician. The three-dimensional point cloud from face model produced with 143-micron accuracy and point clouds of similar faces were registered together in the range of 2mm to 3 mm in rmse.