Object extraction from T2 weighted brain MR image using histogram based gradient calculation
Pattern Recognition Letters
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In this paper, we explored the automatic thickness measurements of pearl from optical coherence tomography (OCT) images. We used a two stage scheme to extract the upper and lower boundaries of nacre respectively, and computed the thickness of nacre based on the extracted upper and lower boundaries. At the first stage, we employed edge detection method to extract the upper boundary. At the following stage, we used pixel classification method to detect the lower boundary. In both stages, boundary refinement and fitting were conducted. The proposed approach is evaluated using pearl optical coherence tomography images, and achieved high segmentation accuracy of 93.56% and relative measurement error of 1.69%. Experimental results demonstrate the effectiveness and robustness of our method.