Automatic fetal biometry prediction using a novel deep convolutional network architecture
- 1 August 2021
- journal article
- research article
- Published by Elsevier in Physica Medica
- Vol. 88, 127-137
Abstract
No abstract availableKeywords
Funding Information
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SNRF 320030_176052)
This publication has 23 references indexed in Scilit:
- Difference of Gaussians revolved along elliptical paths for ultrasound fetal head segmentationComputerized Medical Imaging and Graphics, 2014
- Application of Adaptive Neuro-Fuzzy Inference System for Prediction of Neutron Yield of IR-IECF Facility in High VoltagesJournal of Fusion Energy, 2013
- Evaluation and Comparison of Current Fetal Ultrasound Image Segmentation Methods for Biometric Measurements: A Grand ChallengeIEEE Transactions on Medical Imaging, 2013
- Statistical methods for assessing agreement between two methods of clinical measurementInternational Journal of Nursing Studies, 2010
- Performance measure characterization for evaluating neuroimage segmentation algorithmsNeuroImage, 2009
- Comparison and Evaluation of Segmentation Techniques for Subcortical Structures in Brain MRI2008
- Direct least square fitting of ellipsesIEEE Transactions on Pattern Analysis and Machine Intelligence, 1999
- Selecting and interpreting measures of thematic classification accuracyRemote Sensing of Environment, 1997
- Normal Fetal Growth Assessment: A Review of Literature and Current PracticeJournal of Diagnostic Medical Sonography, 1995
- Measures of the Amount of Ecologic Association Between SpeciesEcology, 1945