CORTICAL BONE SEGMENTATION USING WATERSHED AND REGION MERGING BASED ON STATISTICAL FEATURES
Abstract: Research on
biomedical image is a subject that attracted many researchers’ interest. This
is because the biomedical image could contain important information to help
analyze a disease. One of the existing researches in his field uses dental
panoramic radiographs image to detect osteoporosis. The analyzed area is the
width of cortical bone. To analyze that area, however, we need to determine the
width of the cortical bone. This requires proper segmentation on the dental
panoramic radiographs image. This study proposed the integration of watershed
and region merging method based on statistical features for cortical bone
segmentation on dental panoramic radiographs. Watershed segmentation process
was performed using gradient magnitude value from the input image. The
watershed image that still has excess segmentation could be solved by region
merging based on statistical features. Statistical features used in this study
are mean, standard deviation, and variance. The similarity of adjacent regions
is measured using weighted Euclidean distance from the statistical feature of
the regions. Merging process was executed by incorporating the background
regions as many as possible, while keeping the object regions from being
merged. The segmentation result has succeeded in forming the contours of the
cortical bone. The average value of accuracy is 93.211%, while the average
value of sensitivity and specificity is 93.858% and respectively.
Author: Mamluatul Hani`ah,
Christian Sri Kusuma Aditya, Aryo Harto, Agus Zainal Arifin
Journal Code: jptkomputergg150011
