By Topic

Backpropagation Neural Network for Motion Analysis on Blood-pool Gated Single Photon Emission Computed Tomography

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)
Yu-Chien Shiau ; Dept. of Nucl. Med., Far Eastern Memorial Hospital ; Shue-Tsun Fan ; Te-Son Kuo ; Shu-Hsun Chu

We used backpropagation neural network for left ventricular motion analysis on Tc-99m labeled RBC blood-pool gated single photon emission computed tomography (GSPECT). Phantom images by the model of solid spheres were generated to simulate the left ventricle. Training data sets were selected from the phantom images. After training, the neural network can perform motion analysis on the phantom images and all series of patients' GSPECT images. The results of motion analysis were displayed in the formats of vector fields superimposed on the original GSPECT images. The GSPECT of one patient with normal left ventricle and two patients with abnormal left ventricular motion were acquired and analyzed. The study showed that back propagation neural network was useful in the evaluation of left ventricular motion in GSPECT images

Published in:

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Date of Conference:

17-18 Jan. 2006