http://iet.metastore.ingenta.com
1887

MR contingency supplement prior for joint estimation of activity and attenuation in non-time-of-flight positron emission tomography/MR

MR contingency supplement prior for joint estimation of activity and attenuation in non-time-of-flight positron emission tomography/MR

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Maximum likelihood reconstruction of activity and attenuation (MLAA) from emission data only suffered from the inherent cross-talk between the estimated attenuation and activity distributions. The authors proposed an improved MLAA algorithm by utilising tissue prior atlas (TPA) and a Gibbs prior as prior knowledge. TPA determines the plausible region for each of the typical attenuation coefficients; hence, it imposes statistical condition as a supplement for the exclusive magnetic resonance (MR) information on the reconstruction process of attenuation map. Therefore, along with the soft tissue distribution provided by the segmentation of MR images, an air mask and a bone probability map breakdown the MR low-signal class into four subclasses in order to favour recognition of air and bone. Estimations on attenuation coefficients are realised as a mixture of pseudo-Gaussian distributions. The proposed algorithm is evaluated using the simulated 3D emission data. The proposed MLAA-TPA algorithm is compared with the MR-MLAA algorithm proposed by Heußer et al. Their results demonstrate that the MR-MLAA algorithm performance depends heavily on the MR segmentation accuracy well handled by MLAA-TPA. The quantification results illustrated that the MLAA-TPA outperformed the MR-MLAA algorithm owing to reduction of misclassification and more precise tissue detection.

References

    1. 1)
    2. 2)
    3. 3)
    4. 4)
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2018.0708
Loading

Related content

content/journals/10.1049/el.2018.0708
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address