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Groupwise Consistent Image Registration — A Crucial Step for the Construction of a Standardized Near Infrared Hyper-spectral Teeth Database

机译:分组一致图像配准-构建标准化近红外高光谱牙齿数据库的关键步骤

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Construction of a standardized near infrared (NIR) hyper-spectral teeth database is a first step in the development of a reliable diagnostic tool for quantification and early detection of dental diseases. The standardized diffuse reflectance hyper-spectral database was constructed by imaging 12 extracted human teeth with natural lesions of various degrees in the spectral range from 900 to 1700 nm with spectral resolution of 10 nm. Additionally, all the teeth were imaged by X-ray and digital color camera. The color and X-ray teeth images were presented to the expert for localization and classification of the dental diseases, thereby obtaining a dental disease gold standard. Accurate transfer of the dental disease gold standard to the NIR images was achieved by image registration in a groupwise manner, taking advantage of the multichannel image information and promoting image edges as the features for the improvement of spatial correspondence detection. By the presented fully automatic multi-modal groupwise registration method, images of new teeth samples can be accurately and reliably registered and then added to the standardized NIR hyper-spectral teeth database. Adding more samples increases the biological and patho-physiological variability of the NIR hyper-spectral teeth database and can importantly contribute to the objective assessment of the sensitivity and specificity of multivariate image analysis techniques used for the detection of dental diseases. Such assessment is essential for the development and validation of reliable qualitative and especially quantitative diagnostic tools based on NIR spectroscopy.
机译:建造标准化的近红外(NIR)超频齿数据库是开发可靠诊断工具的第一步,用于量化和早期检测牙科疾病。标准化漫反射率超光谱数据库由成像12提取的人齿构成,利用频谱范围内的各种度的自然病变,从900至1700nm的频谱分辨率为10nm。另外,所有牙齿都由X射线和数字彩色相机成像。呈现给牙科疾病的本地化和分类专家的颜色和X射线图像,从而获得牙科疾病金标准。通过以GroupWise的方式通过图像登记实现牙科疾病金标准的牙科疾病金标准,利用多通道图像信息和促进图像边缘作为用于改善空间对应检测的特征来实现。通过呈现的全自动多模态扩展方法,可以精确且可靠地登记新齿样本的图像,然后添加到标准化的NIR超频齿数据库中。添加更多样品增加了NIR超光谱牙齿数据库的生物和病理生理变异性,并且可以重要地有助于对用于检测牙科疾病的多变量图像分析技术的敏感性和特异性的客观评估。这种评估对于基于NIR光谱的可靠性定性和尤其是定量诊断工具的开发和验证至关重要。

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