@inproceedings{margeta2014decision,
author = {Margeta, J. and McLeod, K. and Criminisi, Antonio and Ayache, N.},
title = {Decision Forests for Segmentation of Left Atrium From 3D MRI},
booktitle = {MICCAI Workshop on Statistical Atlases and Computational Models of the Heart (STACOM)},
year = {2014},
month = {October},
abstract = {In this paper we present a method for fully automatic left atrium segmentation from 3D cardiac magnetic resonance datasets. We propose a machine learning approach using decision forests that requires very few assumptions on the segmentation problem. First, we extract the blood pool using a simple thresholding technique. Then, we learn to separate the left atrium from other structures in the image by using context-rich features applied on images enhanced with a multi-scale vesselness filter and transformed to measure distance to blood pool surface. We present our results on the STACOM LA Segmentation Challenge 2013 validation datasets.},
url = {http://approjects.co.za/?big=en-us/research/publication/decision-forests-for-segmentation-of-left-atrium-from-3d-mri/},
}