Work

A General Formula for Fan‐Beam Lambda Tomography

Year: 2007

Type: article

Abstract: Lambda tomography (LT) is to reconstruct a gradient-like image of an object only from local projection data. It is potentially an important technology for medical X-ray computed tomography (CT) at a reduced radiation dose. In this paper, we prove the first general formula for exact and efficient fan-beam LT from data collected along any smooth curve based on even and odd data extensions. As a result, an LT image can be reconstructed without involving any data extension. This implies that structures outside a scanning trajectory do not affect the exact reconstruction of points inside the trajectory even if the data may be measured through the outside features. The algorithm is simulated in a collinear coordinate system. The results support our theoretical analysis.

Source: International Journal of Biomedical Imaging

DOI: 10.1155/2007/95295

Authors: Hengyong Yu, Ge Wang

Institutions: Virginia Tech - Wake Forest University School of Biomedical Engineering & Sciences, Virginia Tech

Language: English

Topic: Medical Imaging Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: gold

Estimated APC paid: $1,000

Funders: National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering