CAJ | 학술논문

分布式多位置散射光谱法从光子在组织中传播的“香蕉”路径这一理论出发，对测量组织的内部信息进行分析，有效消除了浅表组织对内部信息测量的干扰。设计了一种半透膜---牛奶双层结构仿体实验，以40组不同浓度的牛奶溶液代表需要被测的组织内部成分，牛奶上方盖以1至5层不同厚度的半透膜代表略有差异的浅表组织厚度干扰信息。通过贴合半透膜对该仿体采集分布式两点位置散射光谱数据样本200例，并以其中一单点位置的光谱数据为对照，均按3∶1的比例用BP神经网络的方法分别对下层牛奶溶液的浓度进行建模和预测。实验结果显示单一位置散射光谱和两点位置散射光谱均达到90％以上的训练拟合率和预测精度，且两点位置散射光谱的预测精度更高，达到98.41％。证明了运用光子传播路径的散射光谱法可实现对底层牛奶溶液浓度的有效预测，消除浅表组织对于测量内部组织成分的影响，且将多点位置考虑到建模过程中可进一步提高预测精度。从而验证了该方法对于在不破坏组织完整性的前提下对组织表层以下内部某种成分或物质浓度进行分析的可行性。
분포식다위치산사광보법종광자재조직중전파적“향초”로경저일이론출발，대측량조직적내부신식진행분석，유효소제료천표조직대내부신식측량적간우。설계료일충반투막---우내쌍층결구방체실험，이40조불동농도적우내용액대표수요피측적조직내부성분，우내상방개이1지5층불동후도적반투막대표략유차이적천표조직후도간우신식。통과첩합반투막대해방체채집분포식량점위치산사광보수거양본200례，병이기중일단점위치적광보수거위대조，균안3∶1적비례용BP신경망락적방법분별대하층우내용액적농도진행건모화예측。실험결과현시단일위치산사광보화량점위치산사광보균체도90％이상적훈련의합솔화예측정도，차량점위치산사광보적예측정도경고，체도98.41％。증명료운용광자전파로경적산사광보법가실현대저층우내용액농도적유효예측，소제천표조직대우측량내부조직성분적영향，차장다점위치고필도건모과정중가진일보제고예측정도。종이험증료해방법대우재불파배조직완정성적전제하대조직표층이하내부모충성분혹물질농도진행분석적가행성。
The present paper describes the design of pellicle-milk double-layer phantom experiment .Milk solution of 40 different concentrations represents internal information of tissue ,1 to 5 pellicle which covers above the milk solution represents interfer-ence information of superficial tissue .The experiment collected 200 scattering spectral data of two positions and took the one sin-gle position spectral group as control ,and then respectively predicted the milk solution concentration on bottom layer with the ratio of 3:1 through the BP neural network method .The experimental results show that single position scattering spectrum and two-position scattering spectrum both reached more than 90% training fitting rates and prediction accuracy ,and the prediction accuracy of two-position scattering spectra is higher ,reaching 98.41% .It was verified by the experimental results that scatter-ing spectrum based on photon dissemination path can efficiently predict the milk solution concentration and eliminate the influence of superficial tissue for measurement of internal organization ,and considering multi-position in modeling process can improve the accuracy of the prediction .This study validates the feasibility of the method for exploring internal information of tissue without damaging tissue integrity .