3D Quantification of Intracerebral Brain Hemorrhage
Researchers
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Doc. Dr. Sven Lončarić, principal researcher
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Dr. Atam P. Dhawan, US co-researcher
Institutions
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Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia
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Department of Electrical Engineering, University of Texas, Arlington, USA
Support
This three-year project is financed by Croatian Ministry of Science and Technology and by National Institutes of Health, USA.
Abstract
Computed tomography (CT) allows three-dimensional (3-D) anatomical imaging of brain abnormalities such as human spontaneous intracerebral brain hemorrhage (ICH). With computerized image analysis, it is feasible to characterize the pathology of a selected volume of interest. The proposed research focuses on 3-D quantitative analysis to study the early evolution of the ICH. The underlying hypothesis is that the ICH volume and structure is related to the mortality and morbidity. Patients having ICH are scanned four times: within three hours after first symptoms, one hour later, eight hours later, and within twenty hours after first sympt oms. During the course of the illness, 3-D changes in ICH volume and structure can be observed and analyzed. The important ICH features are volume, position in space, and shape of primary and edema region. The preliminary studies indicate that the ICH volume is significant for the survival of the patient. The position in space must be measured with respect to an invariant 3-D coordinate system so that the movement of the ICH accross the scans can be determined. To achieve invariance it is necessary to perform registration of brain CT images from two scans. We have recently developed an Iterative Principal Axes Registration (IPAR) algorithm to register 3-D multi-modality brain images. We have also developed 3-D spatially weighted region growing algorithms with adaptive clustering for segmentation of ICH regions. Finally, shape features will be computed to correlate the shape evolution of the ICH to mortality and morbidity. In addition, the characteristic behavior of ICH can be correlated with the patient response to the medical treatment with the purpose of evaluating the treatment earlier during the course of the illness. It is expected that the proposed research would provide a computerized system for analysis of the ICH through the characteristic changes in ICH volume and structure during the course of the illness.
Research activities
The research activities on the project can be divided into several main groups:
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Segmentation of CT head images
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Interpolation of segmented images
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Quantitative analisys
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Visualization of the segmentation results
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Statistical analisys
Results
During this project graphical user interface has been developed to provide neuroradiologist easier and more pleasent tool for their research work. The GUI has been developed in the Tcl/Tk script language. The segmentation results were then converted into the Virtual Reality Modeling Language (VRML) files. Binary volume is converted into poligons with the marching cubes algorithm.
Figure 2. Segmentation results: First row: Original image, skull, hemorrhage, brain, background, and calcications; Second row: hemorrhage
after renement, edema segmentation results.
Publications
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A Method for Automatic ICH Segmentation of CT Head Images, D. Cosic and S. Loncaric
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A Rule-based Expert System for ICH Segmentation, D. Cosic and S. Loncaric,6th Conference on Artificial Intelligence in Medicine Europe, Grenoble, France, 1997.
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Segmentation of CT Head Images, S. Loncaric and D. Cosic and A. P. Dhawan, Computer Assisted Radiology '96 - Proceedings of the International Symposium on Computer and Communication Systems for Image Guided Diagnosis and Therapy, pp. 1012-1012, Paris, France, 1996.
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Hierarchical Segmentation of CT Head Images, S. Loncaric and D. Cosic and A. P. Dhawan, Conference Proceedings of the 18th Annual International Conference of IEEE Engineering in Medicine and Biology Society, Amsterdam, Netherlands, 1996.
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Two Methods for ICH Segmentation, D. Cosic and S. Loncaric, Proceedings of the 11th International Symposium on Biomedical Engineering, pp. 63-66, Zagreb, Croatia, 1996.
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New Methods for Cluster Selection in Unsupervised Fuzzy Clustering, D. Cosic and S. Loncaric, Proceedings of the 41th Conference KoREMA'96, vol. 4, pp. 1-3, Opatija, Croatia, 1996.