Abstract

Several scoliosis detection systems, using three-dimensional (3D) cameras or sensors, have been developed in recent years. Because these systems require specific 3D digital cameras or sensors, and the equipment is expensive, they are rarely used in many countries and regions. The development of a scoliosis screening system that uses standard two-dimensional (2D) digital cameras that come with tablet personal computers (PCs) and smartphones will facilitate the efforts made to detect scoliosis patients on a global scale. The aim of this technical note was to report on a mobile application for scoliosis screening that uses a standard 2D digital camera. The subjects were patients aged 10 years or older who visited our outpatient clinic for scoliosis or suspected scoliosis and underwent whole-spine radiography. Photographs of subjects were obtained using a standard 2D digital camera connected to a tablet PC. For analysis, we used the simplified scoliosis diagnosis support application (Cobb First, Its Corporation, Kawasaki, Japan) which operates on Windows 10 operating system (OS). When an image was imported into the application, it was displayed within a grid. The grid consisted of four columns and 40 rows and was divided into 160 areas. Each image was converted into binarized image data by demarcating skin and background color. The image of the subject was displayed as a black subject on a white background. Two types of conditions were presented to process differences in the environment versus skin color. A binarized image with a clear outline was selected. The determination was displayed as a percentage of the black area in each grid. In each row of the grid, the left and right sides of the black area were compared, and the part with the larger area with respect to the opposite side was colored and displayed. Depending on the ratio of the difference, it was possible to display green, yellow, and red. If this mobile application is available for clinical use, it has the potential to improve the accuracy of screening by physicians and nurses. Furthermore, it may also be used globally to check for possible evidence of scoliosis at home to facilitate the early detection of patients who require a medical checkup for scoliosis. Although it is essential to perform a radiographic examination for the definitive diagnosis of scoliosis, our future goal is to limit radiation exposure and replace a radiologic method with one based on a tablet PC or smartphone. A mobile application using a standard 2D digital camera may improve the accuracy of screening scoliosis by physicians and may have global application in home environments.

Highlights

  • Scoliosis screening has been enforced as part of healthcare in schools because of the importance of early detection of scoliosis in teenagers

  • The development of a scoliosis screening system that uses standard two-dimensional (2D) digital cameras that come with tablet personal computers (PCs) and smartphones will facilitate the efforts made to detect scoliosis patients on a global scale

  • Photographs of subjects were obtained using a standard 2D digital camera connected to a tablet PC

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Summary

Introduction

Scoliosis screening has been enforced as part of healthcare in schools because of the importance of early detection of scoliosis in teenagers. The development of a scoliosis screening system that uses standard two-dimensional (2D) digital cameras that come with tablet personal computers (PCs) and smartphones will facilitate the efforts made to detect scoliosis patients on a global scale. The aim of this technical note was to report on a mobile application for scoliosis screening that uses a standard 2D digital camera. The distance between the camera and the subject was not fixed; the area from the neck to the intergluteal cleft was photographed Both upper limbs were positioned so that the shoulders were abducted to approximately 30 degrees in order to provide an unobstructed lateral view of the trunk. Depending on the ratio of the difference, it was possible to display green, yellow, and red (Figures 5 and 6).

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