Title :
Maximum likelihood reconstruction for tomosynthesis
Author :
Chen, Pei ; Barner, Kenneth
Author_Institution :
Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA
Abstract :
We present a maximum likelihood(ML) algorithm for tomosynthesis that reconstructs a 3D radiation attenuation coefficient map from a set of radiograms taken from various view angles. The ML algorithm is developed based on the Poisson model of two dimensional radiography. The ML reconstruction yields better image quality with fewer artifacts than the wildly used filtered backprojection (FBP) reconstruction. Finally, we show representative results on simulated data.
Keywords :
Poisson distribution; diagnostic radiography; image reconstruction; maximum likelihood detection; medical image processing; 3D radiation attenuation coefficient map reconstruction; Poisson model; artifacts; filtered backprojection reconstruction; image quality; maximum likelihood reconstruction; simulated data; three dimensional medical imaging technique; tomosynthesis; two dimensional radiography; view angles; Attenuation; Biomedical imaging; Computed tomography; Image quality; Image reconstruction; Imaging phantoms; Iterative algorithms; Maximum likelihood estimation; Medical simulation; Radiography;
Conference_Titel :
Bioengineering Conference, 2003 IEEE 29th Annual, Proceedings of
Print_ISBN :
0-7803-7767-2
DOI :
10.1109/NEBC.2003.1215991
