本文選題：法庭放射學(xué) + 身高推算��； 參考：《四川大學(xué)》2006年碩士論文

【摘要】：【目的】應(yīng)用放射學(xué)方法，測(cè)量活體人群胸、腰段長(zhǎng)度和腰椎椎體高度，建立適合當(dāng)代中國(guó)漢族人群胸、腰段長(zhǎng)度及腰椎椎體高度推算身高的數(shù)學(xué)模型，為我國(guó)法醫(yī)學(xué)積累基礎(chǔ)數(shù)據(jù)。【方法】 應(yīng)用計(jì)算機(jī)X線攝影(computed radiography，CR)放射學(xué)方法測(cè)量活體腰椎椎體高度與腰段長(zhǎng)度，及數(shù)字X線攝影(digitalradiograph，DR)放射學(xué)方法測(cè)量活體胸段長(zhǎng)度。同時(shí)準(zhǔn)確測(cè)量身高，用SPSS11.5統(tǒng)計(jì)軟件進(jìn)行線性回歸分析，建立回歸方程，另用新鮮樣本進(jìn)行回代，檢驗(yàn)回歸方程的效能。【結(jié)果】 ①建立胸腰椎推算身高的一元回歸方程175個(gè)，多元回歸方程686個(gè)，所有回歸方程經(jīng)線性回歸模型假設(shè)檢驗(yàn)的方差分析，，均有統(tǒng)計(jì)學(xué)意義；②建立的回歸方程的復(fù)相關(guān)系數(shù)(R)在0.408-0.853范圍內(nèi)，回歸方程標(biāo)準(zhǔn)誤差(SE)在2.982cm-7.018cm范圍。③另用124例腰段新鮮樣本和150例胸段新鮮樣本，進(jìn)行回歸方程回代，均證實(shí)胸腰段長(zhǎng)度推算身高的回歸方程具有較好的效能�！窘Y(jié)論】 ①單個(gè)測(cè)量指標(biāo)推算身高的一元回歸方程中，腰段長(zhǎng)度與身高的相關(guān)性最好，其次為胸段長(zhǎng)度。椎體中央高度與身高的相關(guān)性大于椎體前、后緣高度。不同測(cè)量指標(biāo)組合建立的回歸方程要優(yōu)于單個(gè)測(cè)量指標(biāo)建
[Abstract]:[objective] to measure the thoracolumbar length and the lumbar vertebra height of the living population by radiologic method, and to establish a mathematical model for estimating the height of the thoracic, lumbar and lumbar vertebrae in contemporary Chinese Han population. To accumulate basic data for forensic medicine in China. [methods] the height and length of lumbar vertebrae in vivo were measured by computer radiography and computed radiography (CRR), and the length of thoracic segment in vivo was measured by digital radiography-DRR. At the same time, the height was accurately measured, the regression equation was established by linear regression analysis with SPSS11.5 statistical software, and the efficiency of the regression equation was tested with fresh samples. [results] 1 A single regression equation was established to calculate the height of thoracolumbar vertebrae, and 175 regression equations were established to calculate the height of thoracolumbar vertebrae. There are 686 multivariate regression equations. The analysis of variance of all regression equations tested by the hypothesis of linear regression model shows that the complex correlation coefficient of regression equation established by statistical significance is in the range of 0.408-0.853. In the 2.982cm-7.018cm range of 3. 3, another 124 fresh samples of lumbar segment and 150 fresh samples of thoracic segment were used to carry out regression equation revision. [conclusion] 1 the correlation between waist length and height is the best, followed by thoracic segment length. [conclusion] 1 among the single regression equations for calculating height, the correlation between waist length and height is the best, followed by thoracic length. The correlation between the height and the central height of the vertebral body is greater than that of the anterior and posterior edge of the vertebral body. The regression equation of different measurement index combinations is better than that of single measurement index.
【學(xué)位授予單位】：四川大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2006
【分類號(hào)】：D919

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