Abstract
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 th 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.
Highlights
We are using Optical Coherence Tomography (OCT) to image structure and function of the developing embryonic heart in avian models
The purpose of our study is to address this limitation by creating an algorithm for noise reduction in OCT images and evaluating its performance both visually and quantitatively through volumetric visualization and image segmentation
Our evaluation was performed using the following data sets (i) (2D + time) data set that consisted of about 500 images from a complete cardiac cycle of a day 2 quail embryo, (ii) (3D + time) data set that consisted of 20 volumes (3 cardiac cycles) of the day 2 quail embryonic heart captured at a rate of 10 volumes/sec, (iii) a single volume 3D data set consisting of 131 2D image slices of a stage 14 quail embryo corresponding to one phase of the cardiac cycle, and (iv) human colonic crypt data set consisting of 600 2D image slices
Summary
We are using Optical Coherence Tomography (OCT) to image structure and function of the developing embryonic heart in avian models. OCT allows one to non-invasively image living hearts with microscopic resolution, and to visually and quantitatively analyze development. Due to the diminutive size and rapid movements of the early embryonic heart, OCT imaging provides a unique ability to study anatomy and function. Noise present in OCT imaging systems [2,3,4,5,6,7,8,9,10,11] limits our ability to interpret, visualize and analyze image data which is crucial to the understanding of early cardiac development. The novelty of our noise reduction technique lies in its ability to optimally reduce noise based on the characteristics of a particular image data set
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