Spatiotemporal reconstruction of the breathing function

Authors:
D. Duong;D. Shastri;P. Tsiamyrtzis;I. Pavlidis
Affiliations:
Department of Computer Science, University of Houston, Houston, TX;Department of Computer and Mathematical Sciences, University of Houston-Downtown, Houston, TX;Department of Statistics, Athens University of Economics and Business, Athens, Greece;Department of Computer Science, University of Houston, Houston, TX
Venue:
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2012

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Abstract

Breathing waveform extracted via nasal thermistor is the most common method to study respiratory function in sleep studies. In essence, this is a temporal waveform of mean temperatures in the nostril region that at every time step collapses two-dimensional data into a single point. Hence, spatial heat distribution in the nostrils is lost along with valuable functional and anatomical cues. This article presents the construction and experimental validation of a spatiotemporal profile for the breathing function via thermal imaging of the nostrils. The method models nasal airflow advection by using a front-propagating level set algorithm with optimal parameter selection. It is the first time that the full two-dimensional advantage of thermal imaging is brought to the fore in breathing computation. This new multi-dimensional measure is likely to bring diagnostic value in sleep studies and beyond.