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Respiratory motion modelling and prediction using probability density estimation

Alnowam, MR, Lewis, E, Wells, K and Guy, M (2010) Respiratory motion modelling and prediction using probability density estimation In: Nuclear Science Symposium and Medical Imaging Conference, 2010-10-30 - 2010-11-06, Knoxville, USA.

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Abstract

One of the current major challenges in clinical imaging is modeling and prediction of respiratory motion, for example, in nuclear medicine or external-beam radio therapy. This paper presents preliminary work in developing a method for modeling and predicting the temporal behavior of the anterior surface position during respiration. This is achieved by tracking the anterior surface during respiration and projecting the captured motion sequence data into a lower dimensional space using Principle Component Analysis and extracting the variation in the Abdominal surface and Thoracic surface separately. Modeling is based on learning the multivariate probability distribution of the motion sequence using a joint Probability Distribution Function (PDF) between the variation of the Thoracic surface and Abdomen surface in the Eigen space. Moreover, the prediction model encodes the amplitude of the variation in the Eigen space for both Thoracic surface and Abdominal surface and the derivative of the variation which reflects the motion path (velocity). The joint Probability Distribution Function (PDF) of the prediction model covers the likelihood of each position/phase configuration and the associated maximum-likelihood motion path. Moreover, feeding the real-time tracking data into the model during nuclear medicine acquisition or external-beam radio therapy will facilitate adjusting the model for any changes and overcome irregularities in the observed respiration cycle.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
AuthorsEmailORCID
Alnowam, MRUNSPECIFIEDUNSPECIFIED
Lewis, EUNSPECIFIEDUNSPECIFIED
Wells, KUNSPECIFIEDUNSPECIFIED
Guy, MUNSPECIFIEDUNSPECIFIED
Date : 2010
Identification Number : 10.1109/NSSMIC.2010.5874231
Additional Information : © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 18 Mar 2016 17:21
Last Modified : 18 Mar 2016 17:21
URI: http://epubs.surrey.ac.uk/id/eprint/771877

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