摘要
利用光学手段对体表组织信息的检测主要有光谱技术(OST)和光学相干层析技术(OCT),OST以无创、快速和灵敏的特点用于化学成分分析;OCT因其高分辨率、断层成像的特点,在组织结构探测上研究广泛。但两种技术只注重单一光谱或图像信息的获取和分析,缺乏多元性和系统性,对组织成分和位置的探测不足,使得临床应用具有局限性。基于此,该文提出体表组织内高谱图技术,得到组织光谱和图像的多元信息,对组织的成分和结构同时系统分析;采用数据挖掘手段,对数据和病症直接分析建模,挖掘出组织的光谱、图像以及二者交互项与疾病的关系。该技术为临床体表疾病的检测提供更多的信息,能够更准确地反应体表组织生理、生化和病理的状况和改变,同时也降低了系统设备成本和简化了操作步骤。
The present paper innovatively proposed the technology using hyperspectral to detect the body surface tissues that can achieve the systemic analysis of composition and structure by obtaining the multiple spectrum and image information simultaneously. Besides, by the method of data mining, the relationships between diseases and the data including the spectrum, image or synentropy were established. This technology provided more information for the disease detection clinically which can reflect accurately the physiological, biochemical and pathological status and the variation of the body surface tissues, by which both the cost of the equipment and the operation steps can be reduced.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2011年第1期201-204,共4页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(60674111
30973964)资助
关键词
高光谱
成分信息
结构信息
数据挖掘
Hyperspectral
Compositional information
Structural information
Data mining
