期刊
OPTICS EXPRESS
卷 16, 期 16, 页码 12313-12333出版社
OPTICAL SOC AMER
DOI: 10.1364/OE.16.012313
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资金
- NCRR NIH HHS [C06 RR12463-01, C06 RR012463] Funding Source: Medline
- NHLBI NIH HHS [R01 HL083048, R01 HL083048-02, R01HL083048, R01 HL083048-01, R01 HL083048-03] Funding Source: Medline
- NIBIB NIH HHS [T32 EB007509-02, T32 EB007509-01, T32 EB007509, T32EB007509] Funding Source: Medline
We are using Optical Coherence Tomography (OCT) to image structure and function of the developing embryonic heart in avian models. Fast OCT imaging produces very large 3D (2D + time) and 4D (3D volumes + time) data sets, which greatly challenge ones ability to visualize results. Noise in OCT images poses additional challenges. We created an algorithm with a quick, data set specific optimization for reduction of both shot and speckle noise and applied it to 3D visualization and image segmentation in OCT. When compared to baseline algorithms (median, Wiener, orthogonal wavelet, basic non-orthogonal wavelet), a panel of experts judged the new algorithm to give much improved volume renderings concerning both noise and 3D visualization. Specifically, the algorithm provided a better visualization of the myocardial and endocardial surfaces, and the interaction of the embryonic heart tube with surrounding tissue. Quantitative evaluation using an image quality figure of merit also indicated superiority of the new algorithm. Noise reduction aided semi-automatic 2D image segmentation, as quantitatively evaluated using a contour distance measure with respect to an expert segmented contour. In conclusion, the noise reduction algorithm should be quite useful for visualization and quantitative measurements (e. g., heart volume, stroke volume, contraction velocity, etc.) in OCT embryo images. With its semi-automatic, data set specific optimization, we believe that the algorithm can be applied to OCT images from other applications. (C) 2008 Optical Society of America.
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