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issn:1618-727
1.  An Image-Based Comprehensive Approach for Automatic Segmentation of Left Ventricle from Cardiac Short Axis Cine MR Images 
Journal of Digital Imaging  2010;24(4):598-608.
Segmentation of the left ventricle is important in the assessment of cardiac functional parameters. Manual segmentation of cardiac cine MR images for acquiring these parameters is time-consuming. Accuracy and automation are the two important criteria in improving cardiac image segmentation methods. In this paper, we present a comprehensive approach to segment the left ventricle from short axis cine cardiac MR images automatically. Our method incorporates a number of image processing and analysis techniques including thresholding, edge detection, mathematical morphology, and image filtering to build an efficient process flow. This process flow makes use of various features in cardiac MR images to achieve high accurate segmentation results. Our method was tested on 45 clinical short axis cine cardiac images and the results are compared with manual delineated ground truth (average perpendicular distance of contours near 2 mm and mean myocardium mass overlapping over 90%). This approach provides cardiac radiologists a practical method for an accurate segmentation of the left ventricle.
doi:10.1007/s10278-010-9315-4
PMCID: PMC3138938  PMID: 20623156
Image segmentation; cardiac imaging; image analysis; left ventricle
2.  Vascular Editor: From Angiographic Images to 3D Vascular Models 
Journal of Digital Imaging  2009;23(4):386-398.
Modern imaging techniques are able to generate high-resolution multimodal angiographic scans. The analysis of vasculature using numerous 2D tomographic images is time consuming and tedious, while 3D modeling and visualization enable presentation of the vasculature in a more convenient and intuitive way. This calls for development of interactive tools facilitating processing of angiographic scans and enabling creation, editing, and manipulation of 3D vascular models. Our objective is to develop a vascular editor (VE) which provides a suitable environment for experts to create and manipulate 3D vascular models correlated with surrounding anatomy. The architecture, functionality, and user interface of the VE are presented. The VE includes numerous interactive tools for building a vascular model from multimodal angiographic scans, editing, labeling, and manipulation of the resulting 3D model. It also provides comprehensive tools for vessel visualization, correlation of 2D and 3D representations, and tracing of small vessels of subpixel size. Education, research, and clinical applications of the VE are discussed, including the atlas of cerebral vasculature. To our best knowledge, there are no other systems offering similar functionality as the VE does.
doi:10.1007/s10278-009-9194-8
PMCID: PMC3046660  PMID: 19350326
Vasculature; vascular editor; vascular model; cerebrovasculature; angiography; 3D imaging (imaging, three-dimensional); brain imaging; computer version
3.  A Medical Imaging and Visualization Toolkit in Java 
Journal of Digital Imaging  2006;19(1):17-29.
Medical imaging research and clinical applications usually require combination and integration of various techniques ranging from image processing and analysis to realistic visualization to user-friendly interaction. Researchers with different backgrounds coming from diverse areas have been using numerous types of hardware, software, and environments to obtain their results. We also observe that students often build their tools from scratch resulting in redundant work. A generic and flexible medical imaging and visualization toolkit would be helpful in medical research and educational institutes to reduce redundant development work and hence increase research efficiency. This paper presents our experience in developing a Medical Imaging and Visualization Toolkit (BIL-kit) that is a set of comprehensive libraries as well as a number of interactive tools. The BIL-kit covers a wide range of fundamental functions from image conversion and transformation, image segmentation, and analysis to geometric model generation and manipulation, all the way up to 3D visualization and interactive simulation. The toolkit design and implementation emphasize the reusability and flexibility. BIL-kit is implemented in the Java language so that it works in hybrid and dynamic research and educational environments. This also allows the toolkit to extend its usage for the development of Web-based applications. Several BIL-kit-based tools and applications are presented including image converter, image processor, general anatomy model simulator, vascular modeling environment, and volume viewer. BIL-kit is a suitable platform for researchers and students to develop visualization and simulation prototypes, and it can also be used for the development of clinical applications.
doi:10.1007/s10278-005-9247-6
PMCID: PMC3043954  PMID: 16323064
Medical imaging; visualization; toolkit; Java; anatomy model
4.  Medical Image Resource Center–making electronic teaching files from PACS  
Journal of Digital Imaging  2004;16(4):331-336.
A picture archive and communications system (PACS) is a rich source of images and data suitable for creating electronic teaching files (ETF). However, the potential for PACS to support nonclinical applications has not been fully realized: at present there is no mechanism for PACS to identify and store teaching files; neither is there a standardized method for sharing such teaching images. The Medical Image Resource Center (MIRC) is a new central image repository that defines standards for data exchange among different centers. We developed an ETF server that retrieves digital imaging and communication in medicine (DICOM) images from PACS, and enables users to create teaching files that conform to the new MIRC schema. We test-populated our ETF server with illustrative images from the clinical case load of the National Neuroscience Institute, Singapore. Together, PACS and MIRC have the potential to benefit radiology teaching and research.
doi:10.1007/s10278-003-1660-0
PMCID: PMC3044074  PMID: 14747933
electronic teaching files; PACS; computer server; Radiological Society of North America; Medical Image Resource Center; medical education

Results 1-4 (4)