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Proceedings Paper

Detectability improvement of early sign of acute stroke on brain CT images using an adaptive partial smoothing filter
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Paper Abstract

Detection of early infarct signs on non-enhanced CT is mandatory in patients with acute ischemic stroke. We present a method for improving the detectability of early infarct signs of acute ischemic stroke. This approach is considered as the first step for computer-aided diagnosis in acute ischemic stroke. Obscuration of the gray-white matter interface at the lentiform nucleus or the insular ribbon has been an important early infarct sign, which affects decisions on thrombolytic therapy. However, its detection is difficult, since the early infarct sign is subtle hypoattenuation. In order to improve the detectability of the early infarct sign, an image processing being able to reduce local noise with edges preserved is desirable. To cope with this issue, we devised an adaptive partial smoothing filter (APSF). Because the APSF can markedly improve the visibility of the normal gray-white matter interface, the detection of conspicuity of obscuration of gray-white matter interface due to hypoattenuation could be increased. The APSF is a specifically designed filter used to perform local smoothing using a variable filter size determined by the distribution of pixel values of edges in the region of interest. By adjusting four parameters of the APSF, an optimal condition for image enhancement can be obtained. In order to determine a major one of the parameters, preliminary simulation was performed by using composite images simulated the gray-white matter. The APSF based on preliminary simulation was applied to several clinical CT scans in hyperacute stroke patients. The results showed that the detectability of early infarct signs is much improved.

Paper Details

Date Published: 20 March 2006
PDF: 8 pages
Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61446Q (20 March 2006); doi: 10.1117/12.654242
Show Author Affiliations
Yongbum Lee, Niigata Univ. (Japan)
Noriyuki Takahashi, Niigata Univ. Graduate School of Health Sciences (Japan)
Sendai City Hospital (Japan)
Du-Yih Tsai, Niigata Univ. (Japan)
Hiroshi Fujita, Gifu Univ. Graduate School of Medicine (Japan)


Published in SPIE Proceedings Vol. 6144:
Medical Imaging 2006: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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