Related references
Note: Only part of the references are listed.Deep Learning for Predicting Enhancing Lesions in Mu pie Sclerosis from Noncontrast MRI
Ponnada A. Narayana et al.
RADIOLOGY (2020)
Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI
Enhao Gong et al.
JOURNAL OF MAGNETIC RESONANCE IMAGING (2018)
Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs
David B. Larson et al.
RADIOLOGY (2018)
Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning
Mizuho Nishio et al.
PLOS ONE (2018)
A comparison of ultrasound with magnetic resonance imaging in the assessment of fetal biometry and weight in the second trimester of pregnancy: An observer agreement and variability study
Jacqueline Matthew et al.
ULTRASOUND (2018)
Normative biometry of the fetal brain using magnetic resonance imaging
Vanessa Kyriakopoulou et al.
BRAIN STRUCTURE & FUNCTION (2017)
Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions
Zeynettin Akkus et al.
JOURNAL OF DIGITAL IMAGING (2017)
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
James H. Cole et al.
NEUROIMAGE (2017)
Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers
James H. Cole et al.
TRENDS IN NEUROSCIENCES (2017)
ISUOG Practice Guidelines: performance of fetal magnetic resonance imaging
D. Prayer et al.
ULTRASOUND IN OBSTETRICS & GYNECOLOGY (2017)
Emphysema Quantification Using Ultralow-Dose CT With Iterative Reconstruction and Filtered Back Projection
Mizuho Nishio et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2016)
Association Between MRI Exposure During Pregnancy and Fetal and Childhood Outcomes
Joel G. Ray et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2016)
Assessment of MRI-Based Automated Fetal Cerebral Cortical Folding Measures in Prediction of Gestational Age in the Third Trimester
J. Wu et al.
AMERICAN JOURNAL OF NEURORADIOLOGY (2015)
Iterative reconstruction technique vs filter back projection: utility for quantitative bronchial assessment on low-dose thin-section MDCT in patients with/without chronic obstructive pulmonary disease
Hisanobu Koyama et al.
EUROPEAN RADIOLOGY (2014)
Fetal Imaging Executive Summary of a Joint Eunice Kennedy Shriver National Institute of Child Health and Human Development, Society for Maternal-Fetal Medicine, American Institute of Ultrasound in Medicine, American College of Obstetricians and Gynecologists, American College of Radiology, Society for Pediatric Radiology, and Society of Radiologists in Ultrasound Fetal Imaging Workshop
Uma M. Reddy et al.
OBSTETRICS AND GYNECOLOGY (2014)
The effect of iterative reconstruction on computed tomography assessment of emphysema, air trapping and airway dimensions
Onno M. Mets et al.
EUROPEAN RADIOLOGY (2012)
Reconstruction of fetal brain MRI with intensity matching and complete outlier removal
Maria Kuklisova-Murgasova et al.
MEDICAL IMAGE ANALYSIS (2012)
Machine learning and radiology
Shijun Wang et al.
MEDICAL IMAGE ANALYSIS (2012)
MRI of normal fetal brain development
D Prayer et al.
EUROPEAN JOURNAL OF RADIOLOGY (2006)
First trimester ultrasound screening is effective in reducing postterm labor induction rates: A randomized controlled trial
KA Bennett et al.
AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY (2004)
Share Paper
