Segmentation of Salivary Glands in Nuclear Medicine Images Using Edge Detection Tools
DOI:
https://doi.org/10.14738/jbemi.32.1702Keywords:
Salivary glands, MatLab, Scintigraphy, MorphologyAbstract
Recognition of the Salivary glands in nuclear medicine examination is very difficult because of unclear borders and existence of noise, which affects the spatial resolution and reduces the diagnostic values of those images Therefore, image-processing programs such as MatLab, has powerful tools, which can use for solving those problems. The Morphology tool frequently applied to this problem. In this paper, I used entropyfilt function to create a texture image. This function returns an array where each output pixel contains the entropy value of the 9-by-9 neighborhood around the corresponding pixel in the salivary glands scintigraphy images. Threshold the rescaled image to segment the textures. A threshold value of 0.8 selected because it was roughly the intensity value of pixels along the boundary between the textures. The segmented images compare the binary image rough Mask to the original image. The quantitative results calculated using a measure of percentage match between ground truth and segmentation results. The percentage match (PM) measure was 99.33 (p ˂0.05) and Corresponding Ratio (CR) was -0.007 p ˂0.05). The proposed method is able to recognize the salivary glands accurately.References
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