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Marking Early Lesions in Labial Colored Dental Images using a Transfer Learning Approach

机译:使用转移学习方法标记唇牙图像的早期病变

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Dental caries, usually known as tooth decay, are prevalent in patients. According to the World Health Organization (WHO) report, a significant chunk of the overall world population suffers from dental caries. It is essential to trace out the dental cavity at every early stage to treat dental disease. It is difficult for physicians to check out the progress of growing early lesions. X-rays are good enough for severe caries but not for very early-stage lesions. Hence optical images play an essential role in the detection of early lesions. Localizing the carious dental region is also crucial as it reduces the physician recognition activity and can be used in computer-aided learning for new medical students. But unfortunately, accurate localization of the carious region from optical images is challenging. In this research, we used transfer learning to detect the carious enamel regions and locate each carious region found in optical tooth images. We consider photographic images to detect and localize carious regions. Our approach gives 95% accurate results. The proposed methodology is not harmful to health, helpful for physicians, and can be used in computer-aided learning.
机译:龋齿,通常被称为蛀牙,患者普遍存在。根据世界卫生组织(世卫组织)报告称,整体世界人口的大量群体遭受龋齿。在每一次早期阶段都必须追踪牙科腔以治疗牙科疾病。医生很难检查生长早期病变的进展情况。对于严重的龋齿而言,X射线足够好,但不是非常早期病变。因此,光学图像在检测早期病变中起重要作用。本地化龋齿牙科区域也至关重要,因为它降低了医生识别活动,可用于新医学生的计算机辅助学习。但不幸的是,从光学图像的龋齿区域的准确定位是具有挑战性的。在这项研究中,我们使用转移学习来检测龋齿珐琅地区并定位在光学齿图像中的每个龋齿区域。我们考虑摄影图像来检测和定位龋齿区域。我们的方法提供了95%的准确结果。拟议的方法对健康无害,有助于医生,并且可以用于计算机辅助学习。

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