TY - GEN
T1 - Endotracheal tube position confirmation system using neural networks
AU - Lederman, Dror
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Endotracheal intubation is a complex medical procedure in which a ventilating tube is inserted into the human trachea. Improper positioning carries potentially fatal consequences and therefore confirmation of correct positioning is mandatory. In this paper we report the results of using a neural networkbased image classification system for endotracheal tube position confirmation. The proposed system comprises a miniature complementary metal oxide silicon sensor (CMOS) attached to the tip of a semi rigid stylet and connected to a digital signal processor (DSP) with an integrated video acquisition component. Video signals are acquired and processed by a confirmation algorithm implemented on the processor. The performance of the proposed algorithm was evaluated using two datasets: a dataset of 250 images of the upper airways. The results, obtained using a leave-one-case-out method, show that the system correctly classified 240 out of 250 (96. 0%).
AB - Endotracheal intubation is a complex medical procedure in which a ventilating tube is inserted into the human trachea. Improper positioning carries potentially fatal consequences and therefore confirmation of correct positioning is mandatory. In this paper we report the results of using a neural networkbased image classification system for endotracheal tube position confirmation. The proposed system comprises a miniature complementary metal oxide silicon sensor (CMOS) attached to the tip of a semi rigid stylet and connected to a digital signal processor (DSP) with an integrated video acquisition component. Video signals are acquired and processed by a confirmation algorithm implemented on the processor. The performance of the proposed algorithm was evaluated using two datasets: a dataset of 250 images of the upper airways. The results, obtained using a leave-one-case-out method, show that the system correctly classified 240 out of 250 (96. 0%).
KW - Endotracheal intubation confirmation
KW - Esophageal intubation detection
KW - Medical image classification
KW - One-lung intubation detection
UR - https://www.scopus.com/pages/publications/84951849335
U2 - 10.1007/978-3-319-23983-5_8
DO - 10.1007/978-3-319-23983-5_8
M3 - Conference contribution
AN - SCOPUS:84951849335
SN - 9783319239811
T3 - Communications in Computer and Information Science
SP - 80
EP - 85
BT - Engineering Applications of Neural Networks - 16th International Conference, EANN 2015, Proceedings
A2 - Iliadis, Lazaros
A2 - Jayne, Chrisina
PB - Springer Verlag
T2 - 16th International Conference on Engineering Applications of Neural Networks, EANN 2015
Y2 - 25 September 2015 through 28 September 2015
ER -