Paper Info
Title
EVALUATION OF MODEL BASED PARAMETRIC IMAGE ESTIMATION IN MIR
Abstract
Multiple-image radiography (MIR), a new X-ray phase sensitive imaging method, can simultaneously produce parametric images of absorption, refraction, and ultra-small-angle scatter. In the past it has been shown that these three parametric images, when compared to conventional X-ray methods (e.g. mammograms), have excellent diagnostic abilities, thanks to an X-ray phase-contrast mechanism and higher-angle scatter rejections. In this paper we present an evaluation of a newly proposed parametric image estimation method based on a physical model of the image formation in MIR. The proposed method employs the fact that the angular intensity profile (AIP) of the measured X-ray, after interaction with the object, can be modeled as a convolution of a Gaussian curve and the intrinsic imaging system AIP. Further, the new estimation method utilizes an iterative conjugate gradients algorithm that, in combination with the model, offers improvement in parametric image estimation accuracy even in the presence of the imaging noise.
Year
DOI
Venue
2007
10.1109/ISBI.2007.356886
Arlington, VA
Keywords
Field
DocType
diagnostic radiography,iterative methods,noise,MIR,X-ray phase sensitive imaging method,X-ray phase-contrast mechanism,angular intensity profile,imaging noise,iterative conjugate gradients algorithm,multiple-image radiography,parametric image estimation
Computer vision,Parametric Image,Pattern recognition,Convolution,Iterative method,Computer science,Refraction,Image formation,Parametric statistics,Radiography,Artificial intelligence,Gaussian function
Conference
ISSN
ISBN
Citations 
1945-7928
1-4244-0672-2
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Luis Carlos Cobo Rus100.34
Jovan G. Brankov28212.09
Cobo, L.C.300.34