Research suggests that plaque morphology plays a crucial role in determining plaque vulnerability. However the relationship between plaque morphology and rupture is still not clearly understood due to the limited information of plaque morphology. The aim of this study is to improve our understanding of the relationship between plaque morphology and rupture, and to use this to predict the risk of plaque rupture from the morphology at the molecular level. This can enable the identification of culprit lesions in clinical situations for assessing plaque rupture risk. Histological assessments were carried out on 18 carotid plaque specimens. The 3-D collagen, lipid and macrophage distributions along the entire length of the plaque were analysed in both ruptured and non-ruptured symptomatic plaques. In addition, plaque morphology on the rupture sites were examined and compared with the surrounding regions. It was found that ruptured plaques had thinner fibrous caps and larger lipid cores compared to non-ruptured plaques. Also, ruptured plaques had lower collagen content compared to non-ruptured plaques, and higher collagen contents upstream compared to downstream region from the plaque throat. At the rupture site there was lower collagen content, and a larger lipid core thickness behind a thin fibrous cap compared with the mean for the longitudinally adjacent and circumferential regions. Macrophage cells were located nearer to the boundary of the luminal wall in ruptured plaques. For both groups, the area occupied by macrophages is greater at the upstream shoulder of the plaque. There is a positive correlation between macrophage area and lipid core area, a negative correlation between macrophage area and collagen content, and between lipid core size and collagen content for both plaque groups. 3D reconstruction of ex-vivo specimens of carotid plaques were carried out by a combined analysis of US imaging and histology. To reconstruct accurate 3D plaque morphology, the non-linear tissue distortion in histological images caused by specimen preparation was corrected by a finite element (FE) based deformable registration procedure. This study shows that it is possible to generate a 3D patient specific plaque model using this method. In addition, the study also quantitatively assesses the tissue distortion caused by histological procedures. It shows that at least 30% tissue shrinkage is expected for plaque tissues. The histology analysis result was also used to evaluate ultrasound (US) tissue characterization accuracy. An ex-vivo 2D ultrasound scan set-up was used to obtain serial transverse images through an atherosclerotic plaque. The different plaque component region obtained from ultrasound images was compared with the associated histology result and photograph of the sections. Plaque tissue characterisation using ex-vivo US can be performed qualitatively, whereas lipid core assessment from ultrasound scan can be semi-quantitative. This finding combined with the negative correlation between lipid core size and collagen content, suggests the ability of US to indirectly quantify plaque collagen content. This study may serve as a platform for future studies on improving ultrasound tissue characterization, and may also potentially be used in risk assessment of plaque rupture.

The main purpose of this work is to reconstruct 3D model of an entire scene byusing two ordinary cameras. We develop a mobile phone application, based onstereo vision and image analysis algorithms, executed either locally or on a remotehost, to calculate the dietary intake using the current questionnaire and the mobilephone photographs. The information of segmented 3D models are used to calculatethe volume -and then the calories- of a person’s daily intake food. The method ischecked using different solid food samples, in different camera arrangements. Theresults shows that the method successfully reconstructs 3D model of different foodsample with high details.

近年來諸多學者專家致力於從多視角影像獲取精確的點雲資訊，並藉由點雲資訊進行三維模型重建等研究，然而透過多視角影像求取三維資訊的精確度仍然有待提升，其中萃取影像對應與重建三維資訊方法，是多視角影像重建三維資訊的關鍵核心，決定點雲資訊的形成方式與成效。 本論文中，我們提出了一套新的方法，由多視角影像之間的幾何關係出發，萃取多視角影像對應與重建三維點，可以有效地改善對應點與三維點的精確度。首先，在萃取多視角影像對應的部份，我們以相互支持轉換、動態高斯濾波法與綜合性相似度評估函數，改善補綴面為基礎的比對方法，提高相似度測量值的辨識力與可信度，可從多視角影像中獲得精確的對應點。其次，在重建三維點的部份，我們使用K均值分群演算法與線性內插法發掘潛在的三維點，讓求出的三維點更貼近三維空間真實物體表面，能在多視角影像中獲得更精確的三維點。 實驗結果顯示，採用本研究所提出的方法進行改善後，在對應點精確度的提升上有很好的成效，所獲得的點雲資訊存在數萬個精確的三維點，而且僅有少數的離群點。 / Recently, many researchers pay attentions in obtaining accurate point cloud data from multi-view images and use these data in 3D model reconstruction. However, this accuracy still needs to be improved. Among these researches, the methods in extracting the corresponding points as well as computing the 3D point information are the most critical ones. These methods practically affect the final results of the point cloud data and the 3D models so constructed. In this thesis, we propose new approaches, based on multi-view geometry, to improve the accuracy of corresponding points and 3D points. Mutual support transformation, dynamic Gaussian filtering, and similarity evaluation function were used to improve the patch-based matching methods in multi-view image correspondence. Using these mechanisms, the discrimination ability and reliability of the similarity function and, hence, the accuracy of the extracted corresponding points can be greatly improved. We also used K-mean algorithms and linear interpolations to find the better 3D point candidates. The 3D point so computed will be much closer to the surface of the actual 3D object. Thus, this mechanism will produce highly accurate 3D points. Experimental results show that our mechanism can improve the accuracy of corresponding points as well as the 3D point cloud data. We successfully generated accurate point cloud data that contains tens of thousands 3D points, and, moreover, only has a few outliers.