Detection of scoliosis in human spine using Cobb angle - Archana Nandibewoor; Aijazahamed Qazi; Neha Pawar; Pushpalatha Nikkam; Abhilash Hegde (Wolters Kluwer Medknow Publications, 2023)
BACKGROUND: The human backbone is the central support structure of the body. It connects different parts of the body. The spine helps in doing various daily activities such as sitting, walking, standing, and bending. Any impairment in the spine causes spinal disease. Scoliosis is an abnormality in the spinal curve. It consists of a lateral curve. The severity of scoliosis is based on the curvature of the spine, which is calculated based on end plates. AIMS AND OBJECTIVES: Scoliosis is measured using the Cobb angle. The most challenging task is to automate the calculation of scoliosis, considering X-rays of the spine as the input image. Once the end plates are detected, the calculation of the Cobb angle becomes easy, and the calculation can be automated. MATERIALS AND METHODS: The proposed method considers X-ray images of the spine. X-ray images of patients who are defective with scoliosis are used to calculate the Cobb angle using the computerized method. The X-ray images of patients include the Cobb angle ranging with different degrees. Here, the Cobb angle with a degree up to 10 is considered normal and above 10° is considered not normal/affected with scoliosis. In the computerized method, Python 3.7.4 software is used for quantifying the Cobb angle of scoliosis. The main objective of finding the Cobb angle using the computerized method is to reduce human intervention while calculating the Cobb angle. Before the processing begins, the most tilted extreme and inferior vertebrae were taken for cropping the region of interest. As X-ray images are prone to noise, a median filter has been used for image smoothing. For the given X-ray to determine horizontal edge detection, a Gaussian derivative with the suitable thresholding and edge extraction structure has been used. The horizontal edge detection method is considered more suitable compared to vertical detection for detecting end plates of the spinal curve in the case of scoliosis and Cobb angle detection. After horizontal edge detection, the Hough transform is used for the detection of vertebrae slopes. After calculating the slopes of vertebrae, the Cobb angle of scoliosis has been calculated. RESULTS: The proposed Hough transform method increases the efficiency of the existing system accuracy from 75%-80% to 80%-85% by making the Cobb angle calculation automated, thereby reducing manual intervention. Further, depending on the severity of the curvature of the spine in detecting scoliosis, treatment may be suggested to the patients. CONCLUSION: The proposed method is used to calculate the Cobb angle using the image processing technique. The X-ray images of the human spine are taken as input images. By cropping the region of interest in the spinal image from end vertebral plates, the Cobb angle is calculated with minimal human intervention. By adjusting the parameters of the above-mentioned technique, more accurate results are obtained. This technique helps in diagnosis and treatment of scoliosis by evaluation of automated Cobb angle.