Computer Control And Image Contrast Enhancement Of Direct Digital Radiography System

With the development of the electronics and computer science, the technology of radiography has also developed fast and obtained more and more applications. Now almost all of the preparative diagnosis have to use radiographic equipment. Among of them, direct digital radiography (DR) is the most popular one. It uses flat panel detector to receive X-ray and transforms X-ray to digital image signals directly. It has mainly significant advantages, such as high image resolution, wide dynamic range, fast imaging speed, low-dose exposure on the human body and low maintenance costs. Therefore, the research and development on DR system have become a hot topic in the field of biomedical engineering recently.But DR system has its own defects. For example, the operators of DR equipments have to adjust several equipment parameters manually during the imaging course, and this will lower the efficiency of DR system obviously. In addition, noises, X-ray source and object motion can also cause DR images fuzzy, and these fuzzy images can not meet the demands of diagnosis. So, the DR images have to be enhanced before transferred to doctors. The research activities included in this thesis are focused on the computer control of DR system and contrast enhancement of DR images.To increase the working efficiency of DR equipment, we design a computer controlled system to control the kickstand motion and high voltage generator. We also define communication protocol to send demands between computer and control cabinet of kickstand. In the generator control domain, we use SedecalSerial ActiveX proposal to realize the communication between computer and generator. In final, we achieve the system self-regulation.Contrast enhancement of DR image is another research object of this thesis. On the basis of analyzing the human vision system and the multi-scale contrast enhancement, a new multi-scale pyramid image enhancement algorithm is proposed. At first, different scale low frequency parts and high frequency parts are got by multi-scale decomposing. Then, the high frequency parts are mapped by a nonlinear function, and the low frequency parts of every level are disposed by histogram equalization. However, the process of enhancement takes much of time because of the fine resolution of DR images. A new method of accelerating DR image enhancement based on Compute Unified Device Architecture (CUDA) is presented in this thesis too. This method completes a large amount of convolution operations in spatial domain involved in the multi-scale pyramid image enhancement algorithm by using the Graphic Processing Unit (GPU).