Lung diaphragm tracking in CBCT images using spatio-temporal MRF

Sundarapandian, Manivannan and Kalpathi, Ramakrishnan and Siochi, Alfredo R C and Kadam, Amrut S (2016) Lung diaphragm tracking in CBCT images using spatio-temporal MRF. In: COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 53 . pp. 9-18.

PDF Com_Med_Ima_Gra_53_9_2016.pdf - Published Version Restricted to Registered users only Download (1MB) | Request a copy

Abstract

In EBRT in order to monitor the intra fraction motion of thoracic and abdominal tumors, one of the standard approaches is to use the lung diaphragm apex as an internal marker. However, tracking the position of the apex from image based observations is a challenging problem, as it undergoes both position and shape variation. The purpose of this paper is to propose an alternative method for tracking the ipsilateral hemidiaphragm apex (IHDA) position on Cone Beam Computed Tomography (CBCT) projection images. A hierarchical method is proposed to track the IHDA position across the frames. The diaphragm state is modeled as a spatio-temporal Markov Random Field (MRF). The likelihood function is derived from the votes based on 4D-Hough space. The optimal state of the diaphragm is obtained by solving the associated energy minimization problem using graph-cuts. A heterogeneous GPU implementation is provided for the method using CUDA framework and the performance is compared with that of CPU implementation. The method was tested using 15 clinical CBCT images. The results demonstrate that the MRF formulation outperforms the full search method in terms of accuracy. The GPU based heterogeneous implementation of the proposed algorithm takes about 25 s, which is 16% improvement over the existing benchmark. The proposed MRF formulation considers all the possible combinations from the 4D-Hough space and therefore results in better tracking accuracy. The GPU based implementation exploits the inherent parallelism in our algorithm to accelerate the performance thereby increasing the viability of the approach for clinical use. (C) 2016 Elsevier Ltd. All rights reserved.

Item Type:	Journal Article
Publication:	COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
Additional Information:	Copy right for this article belongs to the PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	28 Oct 2016 07:08
Last Modified:	28 Oct 2016 07:08
URI:	http://eprints.iisc.ac.in/id/eprint/55136

Actions (login required)

View Item