11093

OpenCL-Accelerated Computation of a 3D SPECT Projection Operator for the Content Adaptive Mesh Model

Francesc Massanes, Jovan G. Brankov
Medical Imaging Research Center, Illinois Institute of Technology, Chicago, IL 60616
12th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2013

@article{massanes2013opencl,

   title={OpenCL-Accelerated Computation of a 3D SPECT Projection Operator for the Content Adaptive Mesh Model},

   author={Massanes, Francesc and Brankov, Jovan G},

   year={2013}

}

Download Download (PDF)   View View   Source Source   

828

views

In this manuscript, we present a preliminary evaluation of a fully 3D projection operator calculation aimed at emission tomography on a non-circular orbit. The proposed methodology uses the content-adaptive mesh model (CAMM) for volumetric data representation. The CAMM is an efficient data representation based on adaptive non-uniform sampling and linear interpolation. The presented projection operator model incorporates the major data degradation models, namely object attenuation and detector-collimator spatial response, referred to as distance dependent blur. The projection operator is calculated using a ray-casting algorithm and can be adjusted to any scanning geometry and collimator design (e.g. parallel, focusing and pinhole). Open CL implementation allows shortening of computation time in comparison to standard single CPU implementation. In this work we successfully tested implementation of the CAMM projection operator by reconstructing images obtained from a realistic data simulation with SIMIND on a non-circular camera orbit. In the future, we will add other collimator designs.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Recent source codes

* * *

* * *

TwitterAPIExchange Object
(
    [oauth_access_token:TwitterAPIExchange:private] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
    [oauth_access_token_secret:TwitterAPIExchange:private] => o29ji3VLVmB6jASMqY8G7QZDCrdFmoTvCDNNUlb7s
    [consumer_key:TwitterAPIExchange:private] => TdQb63pho0ak9VevwMWpEgXAE
    [consumer_secret:TwitterAPIExchange:private] => Uq4rWz7nUnH1y6ab6uQ9xMk0KLcDrmckneEMdlq6G5E0jlQCFx
    [postfields:TwitterAPIExchange:private] => 
    [getfield:TwitterAPIExchange:private] => ?cursor=-1&screen_name=hgpu&skip_status=true&include_user_entities=false
    [oauth:protected] => Array
        (
            [oauth_consumer_key] => TdQb63pho0ak9VevwMWpEgXAE
            [oauth_nonce] => 1487903266
            [oauth_signature_method] => HMAC-SHA1
            [oauth_token] => 301967669-yDz6MrfyJFFsH1DVvrw5Xb9phx2d0DSOFuLehBGh
            [oauth_timestamp] => 1487903266
            [oauth_version] => 1.0
            [cursor] => -1
            [screen_name] => hgpu
            [skip_status] => true
            [include_user_entities] => false
            [oauth_signature] => qG83Jhy+41z5ZSHJVAWjfN30LCk=
        )

    [url] => https://api.twitter.com/1.1/users/show.json
)
Follow us on Facebook
Follow us on Twitter

HGPU group

2173 peoples are following HGPU @twitter

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: