Imperial College London

ProfessorDanielRueckert

Faculty of EngineeringDepartment of Computing

Head of Department of Computing
 
 
 
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Contact

 

+44 (0)20 7594 8333d.rueckert Website

 
 
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Location

 

568Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Bai:2013:10.1109/TMI.2013.2256922,
author = {Bai, W and Shi, W and O'Regan, DP and Tong, T and Wang, H and Jamil-Copley, S and Peters, NS and Rueckert, D},
doi = {10.1109/TMI.2013.2256922},
journal = {IEEE Transactions on Medical Imaging},
pages = {1302--1315},
title = {A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: application to cardiac MR images},
url = {http://dx.doi.org/10.1109/TMI.2013.2256922},
volume = {32},
year = {2013}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The evaluation of ventricular function is important for the diagnosis of cardiovascular diseases. It typically involves measurement of the left ventricular (LV) mass and LV cavity volume. Manual delineation of the myocardial contours is time-consuming and dependent on the subjective experience of the expert observer. In this paper, a multi-atlas method is proposed for cardiac magnetic resonance (MR) image segmentation. The proposed method is novel in two aspects. First, it formulates a patch-based label fusion model in a Bayesian framework. Second, it improves image registration accuracy by utilizing label information, which leads to improvement of segmentation accuracy. The proposed method was evaluated on a cardiac MR image set of 28 subjects. The average Dice overlap metric of our segmentation is 0.92 for the LV cavity, 0.89 for the right ventricular cavity and 0.82 for the myocardium. The results show that the proposed method is able to provide accurate information for clinical diagnosis.
AU - Bai,W
AU - Shi,W
AU - O'Regan,DP
AU - Tong,T
AU - Wang,H
AU - Jamil-Copley,S
AU - Peters,NS
AU - Rueckert,D
DO - 10.1109/TMI.2013.2256922
EP - 1315
PY - 2013///
SN - 0278-0062
SP - 1302
TI - A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: application to cardiac MR images
T2 - IEEE Transactions on Medical Imaging
UR - http://dx.doi.org/10.1109/TMI.2013.2256922
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000321220300012&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://ieeexplore.ieee.org/document/6494647
UR - http://hdl.handle.net/10044/1/77207
VL - 32
ER -