Open AccessSemi-Automatic Image Segmentation on X-ray Image of Spine using Active Contour Method
Author(s) -
Tri Arief Sardjono,
Ahmad Fauzi Habiba Chozin,
Mohammad Nuh
Publication year - 2021
Publication title -
jaree (journal on advanced research in electrical engineering)
Language(s) - English
Resource type - Journals
eISSN - 2580-0361
pISSN - 2579-6216
DOI - 10.12962/jaree.v5i2.166
Subject(s) - artificial intelligence , active contour model , computer vision , computer science , segmentation , image segmentation , histogram equalization , preprocessor , scale space segmentation , process (computing) , grayscale , histogram , pattern recognition (psychology) , image (mathematics) , operating system
Currently, many image analysis methods have been developed on X-Ray of scoliotic patients. However, segmentation of spinal curvature is still a challenge, and needs to be improved. In this research, we proposed a semi-automatic spinal image segmentation of scoliotic patients from X-Ray images. This method is divided into 2 steps: preprocessing and segmentation process. A conversion process from RGB to grayscale and CLAHE (Contrast Limited Adequate Histogram Equalization) method was used in image preprocessing. The active contour method was used for the segmentation process. The result shows that segmentation of spinal X-ray images of scoliotic patients using active contour method interactively, can give better results. The average of ME and RAE values are 12.98% and 26.75 %. instead of using the interactive region splitting method which gets 21.17% and 89.27%. Keywords: active contour, interactive segmentation, pre-processing, scoliosis.