By Topic

Cross-validation stopping rule for ML-EM reconstruction of dynamic PET series: effect on image quality and quantitative accuracy

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Selivanov, V.V. ; Dept. of Nucl. Med. & Radiobiol., Sherbrooke Univ., Que., Canada ; Lapointe, D. ; Bentourkia, M. ; Lecomte, R.

A major shortcoming of the maximum likelihood expectation maximization (ML-EM) method for reconstruction of dynamic positron emission tomography (PET) images is to decide when to stop the iterative process for image frames with largely different statistics and activity distributions. A widespread practice to overcome this problem involves overiteration of an image estimate followed by smoothing. Here, the authors investigate the qualitative and quantitative accuracy of the cross-validation procedure (CV) as a stopping rule, in comparison to overiteration and post-filtering, for the reconstruction of phantom and small animal dynamic 18F-fluorodeoxyglucose PET data acquired in two-dimensional mode. The CV stopping rule ensured visually acceptable image estimates with balanced resolution and noise characteristics. However, quantitative accuracy required some minimum number of counts per image. The effect of the number of ML-EM iterations on time-activity curves and metabolic rates of glucose extracted from image series is discussed. A dependence of the CV defined number of iterations on projection counts was found that simplifies reconstruction and reduces computation time

Published in:

Nuclear Science, IEEE Transactions on  (Volume:48 ,  Issue: 3 )