Elisenda Bonet-Carne
Elisenda Bonet-Carne
Scientific Manager - BCNatal Fetal Medicine Research Center
Verified email at - Homepage
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Quantitative ultrasound texture analysis of fetal lungs to predict neonatal respiratory morbidity
E Bonet‐Carne, M Palacio, T Cobo, A Perez‐Moreno, M Lopez, ...
Ultrasound in Obstetrics & Gynecology 45 (4), 427-433, 2015
Fetal Brain MRI Texture Analysis Identifies Different Microstructural Patterns in Adequate and Small for Gestational Age Fetuses at Term
M Sanz-Cortés, F Figueras, E Bonet-Carne, N Padilla, V Tenorio, ...
Fetal Diagnosis and Therapy 33 (2), 122-129, 2013
Prediction of neonatal respiratory morbidity by quantitative ultrasound lung texture analysis: a multicenter study
M Palacio, E Bonet-Carne, T Cobo, A Perez-Moreno, J Sabrià, J Richter, ...
American journal of obstetrics and gynecology 217 (2), 196. e1-196. e14, 2017
VERDICT MRI for prostate cancer: intracellular volume fraction versus apparent diffusion coefficient
EW Johnston, E Bonet-Carne, U Ferizi, B Yvernault, H Pye, D Patel, ...
Radiology 291 (2), 391-397, 2019
INNOVATE: A prospective cohort study combining serum and urinary biomarkers with novel diffusion-weighted magnetic resonance imaging for the prediction and characterization of …
E Johnston, H Pye, E Bonet-Carne, E Panagiotaki, D Patel, M Galazi, ...
BMC cancer 16 (1), 1-11, 2016
Performance of an automatic quantitative ultrasound analysis of the fetal lung to predict fetal lung maturity
M Palacio, T Cobo, M Martínez-Terrón, GA Rattá, E Bonet-Carné, ...
American journal of obstetrics and gynecology 207 (6), 504. e1-504. e5, 2012
Feasibility and reproducibility of fetal lung texture analysis by automatic quantitative ultrasound analysis and correlation with gestational age
T Cobo, E Bonet-Carne, M Martínez-Terrón, A Perez-Moreno, N Elías, ...
Fetal diagnosis and therapy 31 (4), 230-236, 2012
Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results
L Ning, E Bonet-Carne, F Grussu, F Sepehrband, E Kaden, J Veraart, ...
Neuroimage 221, 117128, 2020
Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes
XP Burgos-Artizzu, D Coronado-Gutiérrez, B Valenzuela-Alcaraz, ...
Scientific Reports 10 (1), 1-12, 2020
Automatic quantitative MRI texture analysis in small-for-gestational-age fetuses discriminates abnormal neonatal neurobehavior
M Sanz-Cortes, GA Ratta, F Figueras, E Bonet-Carne, N Padilla, A Arranz, ...
PloS one 8 (7), e69595, 2013
Transmission of SARS-CoV-2 infection among children in summer schools applying stringent control measures in Barcelona, Spain.
I Jordan, MF de Sevilla, V Fumado, Q Bassat, E Bonet-Carne, C Fortuny, ...
Clin. infect. dis, 2021
Correlation between a semiautomated method based on ultrasound texture analysis and standard ultrasound diagnosis using white matter damage in preterm neonates as a model
V Tenorio, E Bonet-Carne, F Botet, F Marques, I Amat-Roldan, E Gratacos
Journal of ultrasound in medicine 30 (10), 1365-1377, 2011
Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age
N Baños, A Perez-Moreno, F Migliorelli, L Triginer, T Cobo, ...
Fetal diagnosis and therapy, 2016
VERDICT‐AMICO: Ultrafast fitting algorithm for non‐invasive prostate microstructure characterization
E Bonet‐Carne, E Johnston, A Daducci, JG Jacobs, A Freeman, ...
NMR in Biomedicine 32 (1), e4019, 2019
Muti-shell diffusion MRI harmonisation and enhancement challenge (MUSHAC): progress and results
L Ning, E Bonet-Carne, F Grussu, F Sepehrband, E Kaden, J Veraart, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2019
Non-invasive quantification of prostate cancer using AMICO framework for VERDICT MR
E Bonet-Carne, A Daducci, P Eleftheria, E Johnston, N Stevens, ...
International Society for Magnetic Resonance in Medicine (ISMRM), 2016
Acquiring and predicting multidimensional diffusion (MUDI) data: an open challenge
M Pizzolato, M Palombo, E Bonet-Carne, CMW Tax, F Grussu, A Ianus, ...
Computational Diffusion MRI, 195-208, 2020
Prostate cancer classification on VERDICT DW-MRI using convolutional neural networks
E Chiou, F Giganti, E Bonet-Carne, S Punwani, I Kokkinos, E Panagiotaki
International Workshop on Machine Learning in Medical Imaging, 319-327, 2018
Correlation of quantitative texture analysis of cranial ultrasound with later neurobehavior in preterm infants
V Tenorio, E Bonet-Carne, F Figueras, F Botet, A Arranz, I Amat-Roldan, ...
Ultrasound in Medicine & Biology 40 (9), 2285-2294, 2014
Image analysis techniques for diagnosing diseases
E Gratacós Solsona, E Bonet Carné, M Palacio Riera, A Pérez Moreno, ...
US Patent App. 15/023,315, 2013
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