3D Segmentation of Medical Images Using a Fast Multistage Hybrid Algorithm |
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Authors: | Lixu Gu Terry Peters |
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Institution: | (1) Computer Sciense, Shanghai Jiaotong University, Shanghai, People’s Republic of China;(2) Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada |
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Abstract: | In this paper, we propose a fast multistage hybrid algorithm for 3D segmentation of medical images. We first employ a morphological
recursive erosion operation to reduce the connectivity between the object to be segmented and its neighborhood; then the fast
marching method is used to greatly accelerate the initial propagation of a surface front from the user defined seed structure
to a surface close to the desired boundary; a morphological reconstruction method then operates on this surface to achieve
an initial segmentation result; and finally morphological recursive dilation is employed to recover any structure lost in
the first stage of the algorithm. This approach is tested on 60 CT or MRI images of the brain, heart and urinary system, to
demonstrate the robustness of this technique across a variety of imaging modalities and organ systems. The algorithm is also
validated against datasets for which “truth” is known. These measurements revealed that the algorithm achieved a mean “similarity
index” of 0.966 across the three organ systems. The execution time for this algorithm, when run on a 550 MHz Dual PIII-based
PC runningWindows NT, and extracting the cortex from brain MRIs, the cardiac surface from dynamic CT, and the kidneys from
3D CT, was 38, 46 and 23 s, respectively. |
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Keywords: | Image guided surgery Recursive erosion Fast marching Morphological reconstruction Recursive dilation Similarity index |
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