Reconstruction and Evaluation of Diffuse Optical Imaging
| Autor: | Liang-Yu Chen, 陳亮瑜 |
|---|---|
| Rok vydání: | 2013 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 101 In this study, we first propose the use of edge-preserving regularization in optimizing an ill-conditioned problem in the reconstruction procedure for diffuse optical tomography to prevent unwanted edge smoothing, which usually degrades the attributes of images for distinguishing tumors from background tissues when using Tikhonov regularization. In the edge-preserving regularization method presented here, a potential function with edge-preserving properties is introduced as a regularized term in an objective function. In order to minimize this proposed objective function, an iterative method solving this optimization problem is presented in which half-quadratic regularization is introduced to simplify the minimization task. Both numerical and experimental data are employed to justify the proposed technique. The reconstruction results indicate that the edge-preserving regularization performs superior to Tikhonov regularization. A flexible edge-preserving regularization algorithm based on the finite element method is proposed to reconstruct the optical-property images of near infrared diffuse optical tomography. This regularization algorithm can easily incorporate with varied weighting functions, such as a generalized Lorentzian function, an exponential function, or a generalized total variation function. To evaluate the performance, results obtained from Tikhonov or edge-preserving regularization are compared with each other. As found, the edge-preserving regularization with the generalized Lorentzian function is more attractive than that with other functions for the estimation of absorption-coefficient images concerning functional tomographic images to discover functional information of tested phantoms/tissues. Based on the concept derived from the subjective contrast detail (CD) analysis, an objective contrast-and-size detail (CSD) analysis for evaluating the image quality of near infrared diffuse optical tomography (NIR DOT) is proposed. We define a measure for numerical CSD analysis based on the resolution estimation of contrast and size. Following that, the contrast-and-size map of resolution can be calculated and displayed for each corresponding image in the map; furthermore, a CSD resolution curve can be characterized by calculating the average value of the projection along the physical quantity/axis (size or contrast). To provide some worked examples about the proposed CSD analysis evaluating the imaging performance of different reconstruction methods, Tikhonov regularization and edge-preserving regularization with different weighting functions were employed. Results suggested that using edge-preserving regularization with the generalized Lorentzian weighting function is the most attractive for the estimation of absorption-coefficient images. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|