Application of Spinal Disorders Detection on X-Ray Images Using Segmentation and K-Means Clustering

Abstract

There are three types of spinal disorders, namely kyphosis, lordosis, and scoliosis. To find out spinal disorders, it is necessary to carry out X-rays from an early age. Spinal disorders are not only found in children but can be found in adolescents, adults, and the elderly. Along with the times, making information technology more sophisticated is the advancement of image processing technology. Image processing can help in the medical field to analyze X-ray results to diagnose internal disorders or diseases. This study makes an application for the detection of spinal disorders with several methods of image segmentation processes and using the k-means clustering algorithm on x-ray images of spinal disorders. This segmentation image processing stage requires five stages of processing including cropping, resizing, median filter, histogram equalization, thresholding, and binary edges, and k-means clustering process as a comparison. This application is expected to be useful in knowing the difference between spinal disorders of lordosis, kyphosis, and scoliosis

E-Commerce Product Recommendation System Using Case-Based Reasoning (CBR) and K-Means Clustering

“…The k-means clustering approach has also received attention in various studies. For example, Khairul et al [11] applied this approach in detecting spinal disorders using X-ray images, while Lompoliuw and Purnomo [12] applied the K-Means algorithm in grouping Covid-19 patients based on the length of recovery. Sahputra et al [13] analyzed the factors that influence public transport passengers to switch to Go-Jek online transportation using the K-Means Clustering method.…”

“…In product recommendation, CBR will use data about user preferences for previous products to recommend appropriate new products [10]. On the other hand, K-Means Clustering is a data clustering method that groups data into groups based on feature similarities [11] [12]. In recommendations, K-Means can be used to group products or users with similar preferences [13].…”

E-Commerce Product Recommendation System Using Case-Based Reasoning (CBR) and K-Means Clustering

“…The k-means clustering approach has also received attention in various studies. For example, Khairul et al [11] applied this approach in detecting spinal disorders using X-ray images, while Lompoliuw and Purnomo [12] applied the K-Means algorithm in grouping Covid-19 patients based on the length of recovery. Sahputra et al [13] analyzed the factors that influence public transport passengers to switch to Go-Jek online transportation using the K-Means Clustering method.…”

“…In product recommendation, CBR will use data about user preferences for previous products to recommend appropriate new products [10]. On the other hand, K-Means Clustering is a data clustering method that groups data into groups based on feature similarities [11] [12]. In recommendations, K-Means can be used to group products or users with similar preferences [13].…”

E-Commerce Product Recommendation System Using Case-Based Reasoning (CBR) and K-Means Clustering

“…The k-means clustering approach has also received attention in various studies. For example, Khairul et al [11] applied this approach in detecting spinal disorders using X-ray images, while Lompoliuw and Purnomo [12] applied the K-Means algorithm in grouping Covid-19 patients based on the length of recovery. Sahputra et al [13] analyzed the factors that influence public transport passengers to switch to Go-Jek online transportation using the K-Means Clustering method.…”

“…In product recommendation, CBR will use data about user preferences for previous products to recommend appropriate new products [10]. On the other hand, K-Means Clustering is a data clustering method that groups data into groups based on feature similarities [11] [12]. In recommendations, K-Means can be used to group products or users with similar preferences [13].…”

E-Commerce Product Recommendation System Using Case-Based Reasoning (CBR) and K-Means Clustering

“…The k-means clustering approach has also received attention in various studies. For example, Khairul et al [11] applied this approach in detecting spinal disorders using X-ray images, while Lompoliuw and Purnomo [12] applied the K-Means algorithm in grouping Covid-19 patients based on the length of recovery. Sahputra et al [13] analyzed the factors that influence public transport passengers to switch to Go-Jek online transportation using the K-Means Clustering method.…”

“…In product recommendation, CBR will use data about user preferences for previous products to recommend appropriate new products [10]. On the other hand, K-Means Clustering is a data clustering method that groups data into groups based on feature similarities [11] [12]. In recommendations, K-Means can be used to group products or users with similar preferences [13].…”