Deep learning in the ultrasound evaluation of neonatal respiratory status

  title={Deep learning in the ultrasound evaluation of neonatal respiratory status},
  author={Michela Gravina and Diego Gragnaniello and Luisa Verdoliva and Giovanni Poggi and Iuri Corsini and Carlo Dani and Fabio Meneghin and Gianluca Lista and Salvatore Aversa and Francesco Raimondi and F. Garcia Migliaro and Carlo Sansone},
  journal={2020 25th International Conference on Pattern Recognition (ICPR)},
Lung ultrasound imaging is reaching growing interest from the scientific community. On one side, thanks to its harmlessness and high descriptive power, this kind of diagnostic imaging has been largely adopted in sensitive applications, like the diagnosis and follow-up of preterm newborns in neonatal intensive care units. On the other side, state-of-the-art image analysis and pattern recognition approaches have recently proven their ability to fully exploit the rich information contained in… 

Figures and Tables from this paper


Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound
A novel deep network, derived from Spatial Transformer Networks, is presented, which simultaneously predicts the disease severity score associated to a input frame and provides localization of pathological artefacts in a weakly-supervised way.
A preliminary study to quantitatively evaluate the development of maturation degree for fetal lung based on transfer learning deep model from ultrasound images
The hypothesis that the development of fetal lung maturation degree can be represented by the texture information from ultrasound images has been preliminarily validated and can be considered by the deep model’s output denoted by the estimated gestational age.
Evaluation of an improved tool for non-invasive prediction of neonatal respiratory morbidity based on fully automated fetal lung ultrasound analysis
The objective of this study was to evaluate the performance of a new version of quantusFLM®, a software tool for prediction of neonatal respiratory morbidity (NRM) by ultrasound, which incorporates a
Visual assessment versus computer-assisted gray scale analysis in the ultrasound evaluation of neonatal respiratory status
A semi quantitative estimate of the degree of neonatal respiratory distress was demonstrated both by a validated scoring system and by computer assisted analysis of the ultrasound scan to help to implement point of care ultrasound diagnostics in the NICU.
Attention-Guided Curriculum Learning for Weakly Supervised Classification and Localization of Thoracic Diseases on Chest Radiographs
A convolutional neural network (CNN) based attention-guided curriculum learning (AGCL) framework is presented, which leverages the severity-level attributes mined from radiology reports to improve the classification and localization performance of thoracic diseases from chest radiographs.
Prediction of neonatal respiratory morbidity by quantitative ultrasound lung texture analysis: a multicenter study
Point-of-care chest ultrasound in the Neonatal Intensive Care Unit
In summary, chest ultrasonography has no ground to replace conventional chest radiology tout court, however, when appropriately applied, a lung ultrasound scan can save time and radiation exposure to achieve a critical diagnosis.
Line Artefact Quantification in Lung Ultrasound Images of COVID-19 Patients via Non-Convex Regularisation
A novel method for line artefacts quantification in lung ultrasound (LUS) images of COVID-19 patients is presented as a non-convex regularisation problem involving a sparsity-enforcing, Cauchy-based penalty function, and the inverse Radon transform.
A Review of Early Experience in Lung Ultrasound in the Diagnosis and Management of COVID-19
Lung Ultrasonography Score to Evaluate Oxygenation and Surfactant Need in Neonates Treated With Continuous Positive Airway Pressure.
The LUS score is well correlated with oxygenation status in both term and preterm neonates, and it shows good reliability to predict surfactant administration in preterm babies with a GA less than 34 weeks under continuous positive airway pressure.