以偏振影像分析小鼠皮膚之張力特性

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姓名

林政傑(Cheng-Chieh Lin) 查詢紙本館藏

畢業系所

光電科學與工程學系

論文名稱

以偏振影像分析小鼠皮膚之張力特性
(Mechanical Properties of the Mice Skin Using Polarization Imaging)

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至系統瀏覽論文 (2025-1-16以後開放)

摘要(中)

早於十九世紀中，人為的力學機制被證實能控制細胞組織型態上的變化及基因的表現，將可能帶來新的醫療方法，生物力學因此蓬勃發展。為了建構生物力學模型，取得活體內的力學資訊極為重要，然而現今量測工具短缺，以往侵入式的量測方法導致活體內的資訊取得不易。
近年來研究指出，在休止期之小鼠皮膚給予適當的張力，可以刺激皮膚毛囊的再生，但是在拉扯皮膚的過程中要給予多大的張力，實際在皮膚上的張力分布又是如何，則必須搭配活體量測工具。
因此本研究藉由Mueller Matrix偏振影像系統，在不同張力下的小鼠後背皮膚，以影像方式記錄不同偏振光入射皮膚後反射或散射的偏振狀態，並計算樣本的Mueller Matrix，同時藉由傳統彈簧的方法，量測當下皮膚的平均張力。由複雜的Mueller Matrix，我們可以透過Mueller Matrix Polar Decomposition (MMPD)還原樣本吸收、去偏振及相位延遲等光學特性，並透過Mueller Matrix Transform (MMT)得到樣本的結構變化與纖維的方向性。依照榮總刺激毛囊配方，皮膚在八日內漸進式拉長，以彈簧測得皮膚長度對張力的曲線，總共八日之張力曲線，張力原本隨皮膚長度增長而非線性緩慢爬升的狀態，轉變為急遽上升的模式。偏振影像顯示，與張力同向的水平偏振入射光經皮膚散射後，在水平偏振態的反射量隨皮膚拉長而增加，反應了纖維受拉扯而指向水平方向時，同方向偏振態的反射量將增強的特徵，此結果建立了線性偏振態與張力關係。此外，我們發現某些偏振狀態的反射量對皮膚長度與張力分別呈正(反)向關係與非線性關係，依此特徵，我們藉由類神經網路的訓練，以偏振狀態的反射量為輸入值，協助歸類皮膚之狀態(天數)，其準確率達八成以上。知道皮膚的狀態後，我們也藉由類神經網路判斷皮膚所處的張力範圍，試圖建立偏振光與張力之關係，重現皮膚上的張力分布。

摘要(英)

As early as mid 19th century artificial mechanics was proved to change cellular morphology and gene expression. This discovery in organisms may be contributed to new medical methods. Therefore, the field of Biomechanics has been improving so far.
Recent research shows that telogen elongation of mice skin under appropriate tension can stimulate the regeneration of hair follicle. In order to resolve how much force should be given and how the skin tension distributed during stretching, we need an in vivo measuring system.
As a consequence, in our study we used Mueller Matrix polarimetry to record the the image of the polarization state after the reflection (or scattering) of the polarized incidence light, and calculate the Mueller Matrix of mice skin. Meanwhile, we used the traditional spring measurement to decide the average skin tension. We can revert the optical diattenuation, depolarization and retardation of the skin by Mueller Matrix Polar Decomposition method and obtain the structure variation and fiber orientation by Mueller Matrix Transform method from complicated Mueller Matrix. According to the regeneration formula by the Taipei Veterans General Hospital, the skin was gradually stretched in eight days, and the strain-stress curves were measured by springs once a day, totally eight curves for each mice. The curves showed that tension grew smoothly and nonlinearly during elongation at first but rapidly increased in the following days. The polarization images demonstrated horizontal incidence light produced more horizontal reflected light as we stretched the skin horizontally. This indicated that the more horizontal orientation of fibers by stretching, the more horizontal reflectance of the horizontal incidence light. This phenomenon builded up the relationship between linear polarized light and the tension. Besides, we found out some reflectance of the polarization state had positive (or negative) and nonlinear relationship with skin length and tension respectively. According to these features, we made reflectance of the polarization be the inputs of neural network and trained the neural network system. The system helped us to determine the condition of the skin and it showed great precision above 80%. We also attempted to determine the tension of the skin by neural network, building up the relationship between polarization and tension and returning the distribution of tension in skin.

關鍵字(中)

★ 皮膚張力
★ Mueller Matrix 偏振影像
★ 活體力學量測
★ 生物力學

關鍵字(英)

★ Skin Tension
★ Mueller Matrix Polarimetry
★ Mechanical Measurements in Vivo
★ Biomechanics

論文目次

目錄
中文摘要 i
Abstract ii
目錄 iv
縮寫表 vi
第一章緒論 1
1-1研究動機與目的 1
1-2文獻回顧與探討 1
1-3 論文架構 6
第二章原理與分析法 7
2-1 偏振特性的原理及分析法 7
2-1-1 Stokes Vector的基本概念 7
2-1-2 Mueller Matrix的特性與量測法 10
2.1-3 Mueller Matrix極分解法 14
2-2皮膚特性 16
2-2-1 皮膚組成結構與力學特性 16
2-2-2 皮膚的光偏振特性 19
2-3 類神經網路分析法 25
第三章實驗與量測法 28
3-1 系統架構 28
3-2 系統校正 29
3-2-1 偏振元件校正 29
3-2-2 光強度校正 30
3-3 樣本備製 30
3-4 量測方法 32
第四章實驗結果分析與討論 35
4-1 張力量測結果 35
4-2 偏振影像結果 39
4-3 MMEs、MMPD與MMT之偏振參數結果 49
4-4 類神經網路應用於判斷皮膚狀態 56
4-5 類神經網路應用於判斷皮膚張力 58
第五章結論 64
參考文獻 65

參考文獻

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指導教授

陳思妤(Szu-Yu Chen)

審核日期

2020-1-17

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