@article {450411,
	title = {AIRWAY LABELING USING A HIDDEN MARKOV TREE MODEL},
	journal = {Proc IEEE Int Symp Biomed Imaging},
	volume = {2014},
	year = {2014},
	month = {2014 Apr},
	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{\textquoteright}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.},
	issn = {1945-7928},
	doi = {10.1109/ISBI.2014.6867931},
	author = {Ross, James C and D{\'\i}az, Alejandro A and Okajima, Yuka and Demian Wassermann and Washko, George R and Dy, Jennifer and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}