Artifacts reduction techniques in X-ray cone-beam computed tomography reconstruction
- CBCT is an important tool in image guided radiation therapy. With the existing reconstruction methods, however, various artifacts arise in the image, which are caused by under-sampled projection data, large-area detector, and/or presence of metal implants in patients. This dissertation addresses issues for improved CBCT image quality and clinical decision making. In practical CBCT systems, a circular trajectory is commonly used to acquire projections and reconstruct the volume. However, incomplete data might be collected in a short scan either because of mechanical constraint or dose reduction consideration. In such situation, FDK algorithm cannot provide an accurate image due to the theoretical limitation. In this dissertation, an iterative optimization using prior knowledge and rigid image registration is proposed to handle the limited angle reconstruction problem. The algorithm is derived based on the prior image constrained compressed sensing (PICCS) framework. The proposed algorithm is experimentally validated and compared with PICCS algorithm and demonstrates superior reconstruction accuracy. Large-area flat panel detector induces more scatter, which results in cupping and shading artifacts in the images. Various scatter correction methods have been proposed to reduce the artifacts from both hardware and software sides, but still suffer clinical applicability. In this dissertation, a single-scan scatter correction method using periphery scatter detection and compressed sensing technique is proposed and tested. The algorithm integrates the scatter measurement/reconstruction and projection acquisition into one scan with simple design of boundary lead blockers. It shows effective scatter artifacts reduction ability as well as promising practical usage for the existing CBCT systems. The presence of metals in patients may cause streaking artifacts in x-ray CT, which has long been recognized as a problem that not only limits the quality of CT images, but also makes dose calculation in radiation therapy planning problematic. In this dissertation, a method for binary reconstruction of metal objects is proposed to serve as the first step of metal artifacts reduction. The boundaries of metallic objects are obtained by using a penalized weighted least-squares algorithm with the adequate intensity gradient-controlled. A series of experimental studies are performed to evaluate the proposed approach, and show that when the projection data are sparse, a non-linear manipulation of projection data can greatly facilitate the binary reconstruction process to achieve accurate binary CT images.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|Stanford University, Department of Electrical Engineering.
|Pauly, John (John M.)
|Pauly, John (John M.)
|Statement of responsibility
|Submitted to the Department of Electrical Engineering.
|Thesis (Ph.D.)--Stanford University, 2014.
- © 2014 by Bowen Meng
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