@conference {473046,
	title = {Airway labeling using a Hidden Markov Tree Model},
	booktitle = {Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium onBiomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on},
	year = {2014},
	pages = {554-558},
	abstract = {We present a novel airway labeling algorithm based on a Hidden Markov Tree Model (HMTM). We obtain a collection of discrete points along the segmented airway tree using particles sampling [1] and establish topology using Kruskal\'s minimum spanning tree algorithm. Following this, our HMTM algorithm probabilistically assigns labels to each point. While alternative methods label airway branches out to the segmental level, we describe a general method and demonstrate its performance out to the subsubsegmental level (two generations further than previously published approaches). We present results on a collection of 25 computed tomography (CT) datasets taken from a Chronic Obstructive Pulmonary Disease (COPD) study.},
	author = {Ross, James C and Diaz, Alejandro A and Okajima, Yuka and Demian Wassermann and Washko, George R and Dy, Jennifer and San Jose Est{\'e}par, Ra{\'u}l}
}