DocumentCode :
2052315
Title :
PI-Line Based Fan-Beam Lambda Imaging without Singularities
Author :
Chen, Lingjian ; Ma, Jianhua ; Chen, Wufan
Author_Institution :
Southern Med. Univ., Guangzhou
Volume :
4
fYear :
2007
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
Since the ionizing radiation may induce cancers and genetic damages in the patient, it is highly desirable to minimize the X-ray dose during a CT scan. As one of the local imaging techniques, the Lambda imaging reduces the X-ray dose and imaging time. But the existence of the singular values results in the low quality of the image. The broad applications of the Pi-lines proof that it can deal with the truncated projections effectively. In this work, we propose a new exact Lambda imaging algorithm based on Wang G´s local imaging method and Pi-lines segment to reconstruct an image with utilizing a Gaussian kernel function convoluting the projection data. We also analyze how to choose the parameters of the Gaussian kernel function. Numerical simulations support our new reconstruction algorithm with high quality reconstruction image.
Keywords :
Gaussian processes; cancer; computerised tomography; diagnostic radiography; image reconstruction; image resolution; medical image processing; CT scan; Gaussian kernel function; Pi-lines segment; X-ray dose minimization; cancer diagnosis; fan-beam lambda imaging algorithm; image quality; image reconstruction algorithm; Cancer; Computed tomography; Data analysis; Genetics; Image reconstruction; Image segmentation; Ionizing radiation; Kernel; Optical imaging; X-ray imaging; PI-line; fan-beam; lambda tomography; singularities; truncations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1522-4880
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2007.4379973
Filename :
4379973
Link To Document :
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