Pose estimation of known objects during transmission tomographic image reconstruction.

Pose estimation of known objects during transmission tomographic image reconstruction. Research Abstract Details 

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Pose estimation of known objects during transmission tomographic image reconstruction. Abstract Text:

Ryan J Murphy,Shenyu Yan,Joseph A O'Sullivan,Donald L Snyder,Bruce R Whiting,David G Politte,Giovanni Lasio,Jeffrey F Williamson,

We address the problem of image formation in transmission tomography when metal objects of known composition and shape, but unknown pose, are present in the scan subject. Using an alternating minimization (AM) algorithm, derived from a model in which the detected data are viewed as Poisson-distributed photon counts, we seek to eliminate the streaking artifacts commonly seen in filtered back projection images containing high-contrast objects. We show that this algorithm, which minimizes the I-divergence (or equivalently, maximizes the log-likelihood) between the measured data and model-based estimates of the means of the data, converges much faster when knowledge of the high-density materials (such as brachytherapy applicators or prosthetic implants) is exploited. The algorithm incorporates a steepest descent-based method to find the position and orientation (collectively called the pose) of the known objects. This pose is then used to constrain the image pixels to their known attenuation values, or, for example, to form a mask on the "missing" projection data in the shadow of the objects. Results from two-dimensional simulations are shown in this paper. The extension of the model and methods used to three dimensions is outlined.

Pose estimation of known objects during transmission tomographic image reconstruction. Publishing Authors By Initials

RJ Murphy,S Yan,JA O'Sullivan,DL Snyder,BR Whiting,DG Politte,G Lasio,JF Williamson,

For similar tomography, x-ray computed research abstracts see: tomography, x-ray computed research

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Pose estimation of known objects during transmission tomographic image reconstruction. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: IEEE transactions on medical imaging

VOLUME: 25

Page Numbers: 1392-404

Journal Abbreviation:

ISSN: 0278-0062

DAY: 3

MONTH: Oct

YEAR: 2006

Pose estimation of known objects during transmission tomographic image reconstruction. Information

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LANGUAGE: eng

NlmUniqueID: 8310780

Pose estimation of known objects during transmission tomographic image reconstruction. Keywords Mesh Terms:

KEYWORDS: Tomography, X-Ray Computed

MESH TERMS: methods

Chemical & Substance for Abstract: Pose estimation of known objects during transmission tomographic image reconstruction. Information

Substance Name: Metals

Registry Number: 0

Grant and Affiliation Information for Pose estimation of known objects during transmission tomographic image reconstruction.

AFFILIATION: Advanced Information Systems, General Dynamics, Ypsilanti, MI 48197, USA. ryan.murphy@gd-ais.com

Country: United States

AGENCY: United States NCI

GRANT: R01 CA75371

ACRONYM: CA

MEDLINETA: IEEE Trans Med Imaging

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