Open AccessLeg Bone Fracture Segmentation and Detection using Advanced Morphological Techniques
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1233.0782s319
Subject(s) - artificial intelligence , fracture (geology) , computer vision , computer science , osteoporosis , segmentation , edge detection , standard deviation , bone fracture , image processing , sensitivity (control systems) , radiology , image (mathematics) , geology , medicine , mathematics , engineering , statistics , pathology , geotechnical engineering , electronic engineering
The bone fracture is the most common problem and is likely to occur due to traumatic incidents like vehicle accidents, sporting injuries or due to conditions like osteoporosis, cancer related to bones. Fracture cannot be viewed by naked eye and so X-ray, CT, ultrasound, MRI images are used to detect it. These images cannot be diagnosed directly and henceforth image processing plays a very important role in fracture detection. This paper presents an image processing technique that uses Laplacian method of edge detection for accurate identification of fractured bone area from the X-ray/CT images. From the fractured bone area several parameters like mean, standard deviation are calculated in order to analyze the accuracy and sensitivity of the used technique. NIVISION assistant software is used and the statistical parameters are calculated.