An Automatic Level Set Based Liver Segmentation from MRI Data Sets

A fast and accurate liver segmentation method is a challenging work in medical image analysis area. Liver segmentation is an important process for computer-assisted diagnosis, pre-evaluation of liver transplantation and therapy planning of liver tumors. There are several advantages of magnetic resonance imaging such as free form ionizing radiation and good contrast visualization of soft tissue. Also, innovations in recent technology and image acquisition techniques have made magnetic resonance imaging a major tool in modern medicine. However, the use of magnetic resonance images for liver segmentation has been slow when we compare applications with the central nervous systems and musculoskeletal. The reasons are irregular shape, size and position of the liver, contrast agent effects and similarities of the gray values of neighbor organs. Therefore, in this study, we present a fully automatic liver segmentation method by using an approximation of the level set based contour evolution from T2 weighted magnetic resonance data sets. The method avoids solving partial differential equations and applies only integer operations with a two-cycle segmentation algorithm. The efficiency of the proposed approach is achieved by applying the algorithm to all slices with a constant number of iteration and performing the contour evolution without any user defined initial contour. The obtained results are evaluated with four different similarity measures and they show that the automatic segmentation approach gives successful results

Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Rainbow Kaposi's Sarcoma-Associated Herpesvirus Revealed Heterogenic Replication with Dynamic Gene Expression.

Molecular mechanisms of Kaposi's sarcoma-associated herpesvirus (KSHV) reactivation have been studied primarily by measuring the total or average activity of an infected cell population, which often consists of a mixture of both nonresponding and reactivating cells that in turn contain KSHVs at various stages of replication. Studies on KSHV gene regulation at the individual cell level would allow us to better understand the basis for this heterogeneity, and new preventive measures could be developed based on findings from nonresponding cells exposed to reactivation stimuli. Here, we generated a recombinant reporter virus, which we named "Rainbow-KSHV," that encodes three fluorescence-tagged KSHV proteins (mBFP2-ORF6, mCardinal-ORF52, and mCherry-LANA). Rainbow-KSHV replicated similarly to a prototype reporter-KSHV, KSHVr.219, and wild-type BAC16 virus. Live imaging revealed unsynchronized initiation of reactivation and KSHV replication with diverse kinetics between individual cells. Cell fractionation revealed temporal gene regulation, in which early lytic gene expression was terminated in late protein-expressing cells. Finally, isolation of fluorescence-positive cells from nonresponders increased dynamic ranges of downstream experiments 10-fold. Thus, this study demonstrates a tool to examine heterogenic responses of KSHV reactivation for a deeper understanding of KSHV replication.IMPORTANCE Sensitivity and resolution of molecular analysis are often compromised by the use of techniques that measure the ensemble average of large cell populations. Having a research tool to nondestructively identify the KSHV replication stage in an infected cell would not only allow us to effectively isolate cells of interest from cell populations but also enable more precise sample selection for advanced single-cell analysis. We prepared a recombinant KSHV that can report on its replication stage in host cells by differential fluorescence emission. Consistent with previous host gene expression studies, our experiments reveal the highly heterogenic nature of KSHV replication/gene expression at individual cell levels. The utilization of a newly developed reporter-KSHV and initial characterization of KSHV replication in single cells are presented