.png){kind=icon}
返回
Tiny a priori knowledge solves the interior problem in computed tomography
.png){kind=icon}
OA
AI
DOI：10.1088/0031-9155/53/9/001.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Based on the concept of differentiated backprojection (DBP) (Noo et al 2004 Phys. Med. Biol. 49 3903, Pan et al 2005 Med. Phys. 32 673, Defrise et al 2006 Inverse Problems 22 1037), this paper shows that the solution to the interior problem in computed tomography is unique if a tiny a priori knowledge on the object f (x, y) is available in the form that f (x, y) is known on a small region located inside the region of interest. Furthermore, we advance the uniqueness result to obtain more general uniqueness results which can be applied to a wider class of imaging configurations. We also develop a reconstruction algorithm which can be considered an extension of the DBP-POCS (projection onto convex sets) method described by Defrise et al (2006 Inverse Problems 22 1037), where we not only extend this method to the interior problem but also introduce a new POCS algorithm to reduce computational cost. Finally, we present experimental results which show evidence that the inversion corresponding to each obtained uniqueness result is stable.
Keyword:
REGIONS-OF-INTEREST
IMAGE-RECONSTRUCTION
TRUNCATED PROJECTIONS
HILBERT TRANSFORM
FAN-BEAM
BACKPROJECTION
CT
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.4
论文数:
1.4W
被引数:
3.1W
机构
引用论文
Efficient correction for CT image artifacts caused by objects extending outside the scan field of view.png)
MEDICAL PHYSICS
MEDICAL PHYSICSIF3.2
PREAI
分享收藏Region of interest reconstruction from truncated data in circular cone-beam CT圆锥束CT中截断数据的感兴趣区域重建
PREAI
分享收藏
查看更多内容