Critical Techniques And Basic Application Development For Medical Images Processing

Medical image processing is a multi-disciplinary subject, which relates to the subjects of digital image processing, computer graphics and some related knowledge of medicine. However, until now most of the clinical physicians can only utilize their experience to analyze the two-dimensional image series obtained by CT and MRI, which might be very limited to determine the perfect spatial location and exact area of the disease. Therefore, there is a crying need to build suitable software system based on common-configuration personal computer, which can be applied to visualize the corresponding three-dimensional images by image reconstruction techniques. Furthermore, through the necessary splitting and some other useful analyses or simulations before the actual operation, the clinical physicians could be more confident about the disease. In brief, study on processing and analysis of medical images is widely used in diagnostic, surgery and radiotherapy planning, and teaching in anatomy, which is of great important significance on science and worthiness in practical applications.The research project is one part of"The Diagnostic and Therapeutic System of Computer Integration", supported by"The Tenth Five Years Constructive Finance"in College of Automation Engineering, NUAA. This dissertation describes the author's work on medical image processing and analysis, including algorithm research and software development. The research focuses on three important research fields: image segmentation, reconstruction and measurement. The main research fields and innovative results in this dissertation focus on the following aspects:1) Two novel segmentation algorithms: gradient vector flow deformable model and improved watershed algorithm, are implemented and applied to segment corpus callosum and astrocytoma, both achieved favorable results. Another automatic segmentation algorithm for color retinal vascular images, whose performance exceeds traditional methods, is proposed to guarantee accuracy, objectivity and practicability.2) On the basis of grid computing, the essence and key techniques of parallel visualization of large medical datasets are discussed based on Intranet and common-configuration computers of hospitals. It is suitable and effective for our countries'most hospitals and is also the outcome of PACS construction. It is demonstrated that this method provide promising and real-time results, which resolve the computational speed, memory requirements and undercapitalization puzzles. 3) The neurite growth of cultured dorsal root ganglion is detected by fluorescent immunocytochemistry treated with nerve regeneration factor in different concentration. A novel method based on triangular prism surface area is introduced to calculate the fractal dimension of the two-dimensional immunofluorescent images. Experimental results demonstrate that this method is easy to understand and convenient to operate, with quantitative results according to observations of microscope.4) The methodology is proposed for image processing and interactive visualization of laser scanning confocal microscopy datasets, including automatic pre-processing and ray-casting reconstruction. The program allows for convenient, fast, interactive examination of unknown cell structures even on common PC, which significantly improve the task of understanding the internal structure of laser scanning confocal microscopy image stacks. Meanwhile, it can be used to visualize dynamically changing temporary structures conveniently in addition to static images.5) A novel method, two-step slices registration and fast Shear-Warp reconstruction, is proposed for serial tissue section images. Based on the elementary result of the principal axes transformation method, the optimal registration result is achieved when the mutual information reaches maximum. An improved Shear-Warp algorithm based on sorted volumetric data structure is applied to reduce the access time of non-contribution data cells and consequently speed up the reconstruction process.6) Several famous foreign image processing software are analyzed and evaluated respectively, and advantages are derived and absorbed from them. Two software systems: medical image processing and analysis system (MIPAS) and vascular image computer assisted analysis tool (VICAAT) are developed based on IDL language, with some examples demonstrated. Modular programming is used to design these systems, which are easier to be modeled, organized, maintained and extended by using encapsulation, inheritance and polymorphism features of objects.The new algorithms and methods built in this dissertation are of important value to theoretical research and clinical application, along with the corresponding software, which provide important tools for medical image processing and analysis.