Region of interest three-dimensional visualization in clinical human CT images sequence

Medical image analysis is more than just algorithms. Visualization of the original image data and processed results, interaction with the data, as well as the data themselves are also important. It has been widely used for demonstrating lesions or their localization in the musculoskeletal system, vascular system, respiratory and alimentary systems. Region of interest (ROI) imaging visualization techniques in computed tomography (CT), which can visualize an ROI image from the CT sequence data set of the ROI, can be used not only for reducing imaging-time but also for potentially increasing clinical analysis accuracy of the particular area images. VC++6.0 with visualization toolkit (VTK) are adopted to reconstruct the 3D images using the 2D CT image sequence in DICOM format. The ROI images visualization by use of the marching cubes (MC) algorithm from the clinical human CT data. The experimental results show that this method is robust, easy to implement and excellent image quality evaluation. Because the proposed method requires minimum visualization data for clinical analysis, it can reduce imaging-time, and has excellent image quality evaluation. These methods can assist doctors to make better and more accurate diagnosis.