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Quantitative ultrasound texture analysis of fetal lungs to predict neonatal respiratory morbidity

Author
Bonet-Carne, E.; Palacio, M.; Cobo, T.; Perez-Moreno, A.; Lopez, M.; Piraquive, J.; Ramirez, J.; Botet, F.; Marques, F.; Gratacos, E.
Type of activity
Journal article
Journal
ULTRASOUND IN OBSTETRICS AND GYNECOLOGY
Date of publication
2015
Volume
45
Number
4
First page
427
Last page
433
DOI
https://doi.org/10.1002/UOG.13441 Open in new window
Repository
http://hdl.handle.net/2117/127009 Open in new window
URL
https://obgyn.onlinelibrary.wiley.com/doi/full/10.1002/uog.13441 Open in new window
Abstract
Objective To develop and evaluate the performance of a novel method for predicting neonatal respiratory morbidity based on quantitative analysis of the fetal lung by ultrasound. Methods More than 13¿000 non-clinical images and 900 fetal lung images were used to develop a computerized method based on texture analysis and machine learning algorithms, trained to predict neonatal respiratory morbidity risk on fetal lung ultrasound images. The method, termed ‘quantitative ultrasound fetal lung mat...
Citation
Bonet-Carne, E., Palacio, M., Cobo, T., Perez-Moreno, A., Lopez, M., Piraquive, J., Ramirez, J., Botet, F., Marques, F., Gratacos, E. Quantitative ultrasound texture analysis of fetal lungs to predict neonatal respiratory morbidity. "ULTRASOUND IN OBSTETRICS AND GYNECOLOGY", 2015, vol. 45, núm. 4, p. 427-433.
Keywords
Fetal lung maturity, Image quantitative analysis, Neonatal respiratory morbidity, Texture analysis
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

  • Bonet-Carne, Elisenda  (author)
  • Palacio, M.  (author)
  • Cobo, T.  (author)
  • Perez-Moreno, A.  (author)
  • Lopez, M.  (author)
  • Piraquive, J.P.  (author)
  • Ramirez, J.C.  (author)
  • Botet, F.  (author)
  • Marques Acosta, Fernando  (author)
  • Gratacos, E.  (author)

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