本文關(guān)鍵詞：顱腦硬膜血腫近紅外光譜無創(chuàng)檢測的最佳S-D分布研究　出處：《天津工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 顱腦硬膜血腫檢測 MC VIP 組織仿體 近紅外光譜

【摘要】：基于近紅外光譜(Near Infrared Spectroscopy,NIRS)的腦血腫無創(chuàng)檢測是生物醫(yī)學(xué)領(lǐng)域中腦科學(xué)研究的重要內(nèi)容。自然災(zāi)害等復(fù)雜環(huán)境下顱腦創(chuàng)傷傷情快速診斷是降低顱腦創(chuàng)傷死亡率的關(guān)鍵,近紅外光譜實(shí)現(xiàn)腦血腫快速診斷,是解決此問題的重點(diǎn)方向之一,目前已有一定研究進(jìn)展,而有關(guān)近紅外光譜檢測顱腦硬膜血腫的最佳光源-檢測器(Source-Detector,S-D)分布的研究還未見發(fā)表,合理準(zhǔn)確的選擇S-D分布可能對顱腦硬膜血腫檢測結(jié)果的準(zhǔn)確度的提升、檢測模型復(fù)雜度降低、腦功能的基礎(chǔ)研究等提供更加豐富關(guān)鍵的參考信息。本文從基于近紅外光密度差異檢測腦血腫的角度出發(fā),以獲得無創(chuàng)顱腦硬膜血腫檢測中最佳S-D分布為研究目標(biāo),在近紅外光檢測顱腦硬膜血腫基礎(chǔ)理論、近紅外光在腦組織中傳輸模型、檢測模型仿真算法的設(shè)計(jì)與驗(yàn)證實(shí)驗(yàn)等方面進(jìn)行了深入的研究。主要內(nèi)容包括:基于Monte Carlo(MC)模型記錄2.5cm、3.0cm、3.5cm、4.0cm、4.5cm位置在不同血腫出現(xiàn)情況下光密度變化,利用偏最小二乘法(Partial Least Square method,PLS)建立基于近紅外光密度差異的顱腦硬膜血腫檢測模型,在檢測顱腦血腫的同時(shí),可對顱腦硬膜血腫程度進(jìn)行預(yù)測;提出近紅外光譜血腫檢測的等效信噪比概念,以此為最佳S-D分布的指導(dǎo)標(biāo)準(zhǔn),進(jìn)行最佳S-D分布仿真研究;引入808nm近紅外光作為參考光,提供先驗(yàn)信息;利用變量投影重要性分析(Variable Importance in the Projection,VIP)對檢測器個數(shù)及分布進(jìn)行了優(yōu)化,降低模型復(fù)雜程度;配制光學(xué)仿體對最佳S-D分布結(jié)果進(jìn)行實(shí)驗(yàn)驗(yàn)證。本文所建立顱腦硬膜血腫程度預(yù)測模型相關(guān)度為88.94%,平均誤差為0.0838cm-1,對樣本數(shù)為16的預(yù)測集進(jìn)行預(yù)測,預(yù)測集相關(guān)度為86.65%,平均誤差為0.1047cm-1;根據(jù)等效信噪比和檢測設(shè)備的信噪比,獲得檢測目標(biāo)深度信息的最佳S-D范圍;利用808nm近紅外光作為參考光,建立針對不同頭皮顱骨厚度最佳S-D位置的預(yù)測模型,訓(xùn)練集模型相關(guān)度為99.1%,平均誤差為0.0291cm,對樣本數(shù)為16的預(yù)測集進(jìn)行預(yù)測,預(yù)測集預(yù)測相關(guān)度為98.8%,平均誤差為0.0323cm;利用VIP分析從2.0-5.0cm范圍內(nèi)30個檢測器中篩選出最佳的4個檢測器(2.1cm、2.4cm、3.4cm、4.2cm),利用篩選出檢測器對血腫程度進(jìn)行預(yù)測,其精度優(yōu)于30個檢測器同時(shí)建模方案以及平均選擇檢測器建模方案;配置4種濃度的光學(xué)仿體進(jìn)行實(shí)驗(yàn),驗(yàn)證了本研究有關(guān)最佳S-D分布的結(jié)果,同時(shí)表明,對于不同頭皮顱骨厚度的顱腦硬膜血腫患者,單組S-D檢測時(shí)會有較大誤差,驗(yàn)證了本研究所提出多通道檢測方案的必要性。
[Abstract]:Noninvasive detection of hematoma based on Near Infrared Spectroscopy (NIRS) is an important part of the research of brain science in the field of biomedicine. Natural disasters and complex environment for rapid diagnosis of craniocerebral injury is the key to reduce the mortality of craniocerebral trauma, rapid diagnosis of cerebral hematoma achieve near infrared spectroscopy is one of the most important directions to solve this problem, there are some research progress, and the optimum source of near infrared spectroscopy to detect intracranial dural hematoma (Source-Detector, S-D) distribution detector the study has not been published, may choose S-D distribution with reasonable accuracy in craniocerebral epidural hematoma the accuracy of detection results, enhance the detection model of reduced complexity, brain function and basic research to provide more abundant key reference information. This article from the near infrared light density difference detection based on the angle of the hematoma, for noninvasive detection of brain hematoma best S-D distribution as the research object, the investigation in the near infrared detection head theory, epidural hematoma in the brain tissue near infrared light transmission model, detection model simulation algorithm design and experimental verification etc.. The main contents include: Based on Monte Carlo (MC) model, 3.0cm, 3.5cm, 2.5cm 4.0cm, 4.5cm position in different changes in optical density of hematoma cases, using partial least squares (Partial Least Square method, PLS) the establishment of near infrared light density difference of cerebral hematoma detection based on the model in the detection of intracranial hematoma at the same time that can predict the degree of brain hematoma; the equivalent SNR concept of near infrared spectrum detection based on optimal hematoma, S-D distribution guidance standard, simulation study on the distribution of S-D; the introduction of 808nm near infrared light as reference light, provide a priori information; variable importance in projection using Importance (Variable in the Projection, VIP) on the number and distribution of detector was optimized to reduce model complexity; preparation of optical phantom of the optimal S-D distribution of the results of an experiment. This brain epidural hematoma degree prediction model of correlation degree is 88.94%, the average error is 0.0838cm-1, the number of samples for prediction set of 16 forecast, prediction correlation degree is 86.65%, the average error is 0.1047cm-1; according to the equivalent SNR and detection equipment SNR, detection target depth information of the optimal range of S-D 808nm; using near infrared light as reference light, for different models of scalp skull thickness best S-D position, the training set model is 99.1%, the average error is 0.0291cm, the number of samples in the prediction set of 16 forecast, set predicted degree is 98.8%, the average error is 0.0323cm; using VIP analysis from the range of 2.0-5.0cm 30 detector selected 4 optimal detectors (2.1cm, 2.4cm, 3.4cm, 4.2cm), were selected by detector to predict hematoma degree, its precision is better than 30 detector At the same time modeling scheme and average detector selection modeling scheme; optical phantoms and 4 concentration experiments were conducted to verify the research about the optimal distribution of S-D results also show that for different thickness of the scalp skull brain hematoma patients, single group S-D test will have a greater error, verify the necessity of the proposed multi channel detection scheme.
【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R651.15;O434.33

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 賀文欽;嚴(yán)文娟;賀國權(quán);楊增寶;譚勇;李剛;林凌;;無創(chuàng)血液成分檢測中基于VIP分析的波長篩選[J];光譜學(xué)與光譜分析;2016年04期

2 唐_";趙晨;陳志彥;李鵬;丁志華;;超高分辨光學(xué)相干層析成像技術(shù)與材料檢測應(yīng)用[J];物理學(xué)報(bào);2015年17期

3 王鈺妍;錢志余;李韙韜;劉洋洋;謝捷如;;基于近紅外光譜技術(shù)的脊椎外科手術(shù)導(dǎo)航路徑光學(xué)參數(shù)研究[J];生物醫(yī)學(xué)工程學(xué)雜志;2015年03期

4 徐剛;李小俚;劉曉民;;簡易腦功能近紅外光譜系統(tǒng)設(shè)計(jì)[J];光譜學(xué)與光譜分析;2015年02期

5 侯永強(qiáng);齊紅基;李煦;何凱;易葵;邵建達(dá);;Phase shift of polarized light through sculptured thin films: Experimental measurements and theoretical study[J];Chinese Physics B;2013年12期

6 王雪娜;李韙韜;錢志余;王新增;;大鼠創(chuàng)傷性腦水腫模型中近紅外光有效檢測深度研究[J];光子學(xué)報(bào);2011年02期

7 曾濤;琚存勇;蔡體久;劉文彬;姚月鋒;;利用變量投影重要性準(zhǔn)則篩選郁閉度估測參數(shù)[J];北京林業(yè)大學(xué)學(xué)報(bào);2010年06期

8 姚俊杰;胡剛;岳蜀華;白凈;;用于熒光分子斷層成像的小動物軀干部分三維表面輪廓重建研究[J];中國生物醫(yī)學(xué)工程學(xué)報(bào);2008年03期

9 丁海曙;騰軼超;;組織血氧參數(shù)近紅外無損檢測技術(shù)及自主創(chuàng)新之路[J];激光與光電子學(xué)進(jìn)展;2007年09期

10 趙會娟;姜穎婷;繆輝;高峰;YUKARI Tanikawa;YUKIO Yamada;;近紅外漫射光層析成像實(shí)驗(yàn)研究[J];光子學(xué)報(bào);2007年06期

相關(guān)會議論文 前1條

1 陳德福;林慧韞;李步洪;謝樹森;;光敏化單態(tài)氧的近紅外發(fā)光成像技術(shù)研究[A];中國光學(xué)學(xué)會2011年學(xué)術(shù)大會摘要集[C];2011年

，

本文編號：1344151