Intensity-Based Image Registration and 3-D Image Denoising

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

This project focuses on two important image analysis problems. One is on image registration, which is to match up images or image volumes for structure localization, difference detection, and other purposes. It is widely used in medical imaging, remote sensing, finger print or face recognition, and so forth. The second major focus is on 3-D image denoising with edges and major edge features preserved. Because of fast progress in image acquisition techniques, 3-D images become increasingly popular in magnetic resonance imaging (MRI), functional MRI (fMRI), and other applications. However, observed 3-D images often contain noise, due to hardware imperfection and other reasons, which should be removed beforehand so that subsequent image analyses would be more reliable. In the literature, existing image registration (IR) methods can be roughly classified into two categories: feature-based IR methods and intensity-based IR methods. Because feature selection is often a time-consuming and challenging process, intensity-based IR methods have become popular in various applications. However, most existing intensity-based IR methods require a parametric model for describing the image matching transformation, which is often difficult to verify in practice. In this project, the investigator and his colleagues propose an intensity-based IR procedure without imposing any parametric form on the matching transformation. Therefore, the proposed method has the potential to greatly improve the intensity-based IR techniques and greatly broaden their applications. In the literature, most existing image denoising methods are for analyzing 2-D images. They often have certain ability to preserve planar parts of the edges, but cannot preserve angular parts of the edges well. Their direct extensions to 3-D cases generally cannot handle 3-D images efficiently, because the structure of 3-D images is often substantially more complicated than that of 2-D images. This project proposes a novel 3-D image denoising method which can preserve edges and major edge features well. Therefore, it would provide a reliable tool for 3-D image denoising. Images are used everywhere in our society, ranging from medical diagnostics by CT, MRI, and other medical imaging techniques to satellite monitoring of global environmental changes. This project aims to improve image registration and 3-D image denoising techniques, which are used broadly in various imaging applications. Thus, it will have broader impacts on our society through its direct impact on improvement of medical diagnostics, security systems involving fingerprint and face recognition, remote sensing techniques, and so forth. This project also aims to contribute to the development of human resources in science and engineering through its educational activities. For instance, the investigator offers an advanced topics course on image analysis, from which graduate students from various departments can receive systematic training in scientific research. Several graduate students are doing their thesis research with the investigator on image processing. Some computer software packages developed by the investigator and his graduate students would be posted on a project web page for other researchers to download and use. The major research results obtained from this project would be presented in national and international conferences, and be submitted for publication in academic journals.