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Ana I. L. Namburete
Ana Ineyda Luisa Namburete
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- affiliation: University of Oxford, Institute of Biomedical Engineering
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2020 – today
- 2025
- [e5]Alberto Gómez
, Bishesh Khanal
Simplifying Medical Ultrasound - 5th International Workshop, ASMUS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings. Lecture Notes in Computer Science 15186, Springer 2025, ISBN 978-3-031-73646-9 [contents] - [e4]Binod Bhattarai, Sharib Ali, Anita Rau, Razvan Caramalau, Anh Nguyen, Prashnna Gyawali, Ana I. L. Namburete
Data Engineering in Medical Imaging - Second MICCAI Workshop, DEMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. Lecture Notes in Computer Science 15265, Springer 2025, ISBN 978-3-031-73747-3 [contents] - 2024
- [j14]Pak-Hei Yeung
Sensorless volumetric reconstruction of fetal brain freehand ultrasound scans with deep implicit representation. Medical Image Anal. 94: 103147 (2024) - [j13]Madeleine K. Wyburd
Anatomically plausible segmentations: Explicitly preserving topology through prior deformations. Medical Image Anal. 97: 103222 (2024) - [c33]Daniel Asfaw, Ivan Jordanov, Lawrence Impey, Ana I. L. Namburete, Raymond Lee, Antoniya Georgieva:
Gated Self Attention Convolutional Neural Networks for Predicting Adverse Birth Outcomes. IIAI-AAI 2024: 259-266 - [c32]Jayroop Ramesh, Nicola K. Dinsdale, Pak-Hei Yeung, Ana I. L. Namburete:
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos. MICCAI (1) 2024: 419-429 - [c31]Linde S. Hesse, Nicola K. Dinsdale, Ana I. L. Namburete:
Prototype Learning for Explainable Brain Age Prediction. WACV 2024: 7888-7898 - [i14]Mark C. Eid, Pak-Hei Yeung, Madeleine K. Wyburd, João F. Henriques, Ana I. L. Namburete:
RapidVol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scans. CoRR abs/2404.10766 (2024) - [i13]Jayroop Ramesh, Nicola K. Dinsdale, INTERGROWTH-21 Consortium, Pak-Hei Yeung, Ana I. L. Namburete:
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos. CoRR abs/2405.13235 (2024) - 2023
- [j12]T. Waddell, Ana I. L. Namburete, Paul Duckworth, N. Eichert, H. Thomaides-Brears
Bayesian networks and imaging-derived phenotypes highlight the role of fat deposition in COVID-19 hospitalisation risk. Frontiers Bioinform. 3 (2023) - [c30]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete:
SFHarmony: Source Free Domain Adaptation for Distributed Neuroimaging Analysis. ICCV 2023: 11460-11471 - [c29]Tom Henry Waddell
The impact of projected increases in obesity prevalence on incident liver disease in the UK: Insights from Bayesian-network modelling. ICMHI 2023: 44-48 - [c28]Andrei Claudiu Roibu
Brain Ages Derived from Different MRI Modalities are Associated with Distinct Biological Phenotypes. SDS 2023: 17-25 - [e3]Binod Bhattarai
Data Engineering in Medical Imaging - First MICCAI Workshop, DEMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14314, Springer 2023, ISBN 978-3-031-44991-8 [contents] - [i12]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete:
SFHarmony: Source Free Domain Adaptation for Distributed Neuroimaging Analysis. CoRR abs/2303.15965 (2023) - [i11]Linde S. Hesse, Nicola K. Dinsdale, Ana I. L. Namburete:
Prototype Learning for Explainable Regression. CoRR abs/2306.09858 (2023) - 2022
- [j11]Nicola K. Dinsdale, Mark Jenkinson
STAMP: Simultaneous Training and Model Pruning for low data regimes in medical image segmentation. Medical Image Anal. 81: 102583 (2022) - [j10]Linde S. Hesse
Subcortical segmentation of the fetal brain in 3D ultrasound using deep learning. NeuroImage 254: 119117 (2022) - [j9]Felipe Moser
BEAN: Brain Extraction and Alignment Network for 3D Fetal Neurosonography. NeuroImage 258: 119341 (2022) - [c27]Pak-Hei Yeung
Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images. MICCAI (4) 2022: 207-217 - [c26]Linde S. Hesse, Ana I. L. Namburete:
INSightR-Net: Interpretable Neural Network for Regression Using Similarity-Based Comparisons to Prototypical Examples. MICCAI (3) 2022: 502-511 - [c25]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete:
FedHarmony: Unlearning Scanner Bias with Distributed Data. MICCAI (8) 2022: 695-704 - [c24]Daniel Asfaw, Ivan Jordanov
Fetal Heart Rate Classification with Convolutional Neural Networks and the Effect of Gap Imputation on Their Performance. LOD (1) 2022: 459-469 - [i10]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete:
FedHarmony: Unlearning Scanner Bias with Distributed Data. CoRR abs/2205.15970 (2022) - [i9]Linde S. Hesse, Ana I. L. Namburete:
INSightR-Net: Interpretable Neural Network for Regression using Similarity-based Comparisons to Prototypical Examples. CoRR abs/2208.00457 (2022) - [i8]Pak-Hei Yeung, Moska Aliasi, Monique C. Haak, Weidi Xie, Ana I. L. Namburete:
Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images. CoRR abs/2209.05477 (2022) - 2021
- [j8]Pak-Hei Yeung
Learning to map 2D ultrasound images into 3D space with minimal human annotation. Medical Image Anal. 70: 101998 (2021) - [j7]Nicola K. Dinsdale, Emma Bluemke, Stephen M. Smith
Learning patterns of the ageing brain in MRI using deep convolutional networks. NeuroImage 224: 117401 (2021) - [j6]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete
Deep learning-based unlearning of dataset bias for MRI harmonisation and confound removal. NeuroImage 228: 117689 (2021) - [c23]Pak-Hei Yeung
Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-supervised Learning. MICCAI (2) 2021: 69-79 - [c22]Madeleine K. Wyburd
Assessment of Regional Cortical Development Through Fissure Based Gestational Age Estimation in 3D Fetal Ultrasound. UNSURE/PIPPI@MICCAI 2021: 242-252 - [c21]Madeleine K. Wyburd, Nicola K. Dinsdale, Ana I. L. Namburete
TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations. MICCAI (1) 2021: 250-260 - [e2]Bartlomiej W. Papiez, Mohammad Yaqub, Jianbo Jiao
Medical Image Understanding and Analysis - 25th Annual Conference, MIUA 2021, Oxford, United Kingdom, July 12-14, 2021, Proceedings. Lecture Notes in Computer Science 12722, Springer 2021, ISBN 978-3-030-80431-2 [contents] - [i7]Pak-Hei Yeung, Ana I. L. Namburete, Weidi Xie:
Sli2Vol: Annotate a 3D Volume from a Single Slice with Self-Supervised Learning. CoRR abs/2105.12722 (2021) - [i6]Nicola K. Dinsdale, Emma Bluemke, Vaanathi Sundaresan, Mark Jenkinson, Stephen M. Smith, Ana I. L. Namburete:
Challenges for machine learning in clinical translation of big data imaging studies. CoRR abs/2107.05630 (2021) - [i5]Madeleine K. Wyburd, Nicola K. Dinsdale, Ana I. L. Namburete, Mark Jenkinson:
TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations. CoRR abs/2107.13542 (2021) - [i4]Pak-Hei Yeung, Linde S. Hesse, Moska Aliasi, Monique C. Haak, Weidi Xie, Ana I. L. Namburete:
ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representation. CoRR abs/2109.12108 (2021) - 2020
- [j5]Sagar Vaze
Low-Memory CNNs Enabling Real-Time Ultrasound Segmentation Towards Mobile Deployment. IEEE J. Biomed. Health Informatics 24(4): 1059-1069 (2020) - [j4]Jianbo Jiao
Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis. IEEE Trans. Medical Imaging 39(12): 4413-4424 (2020) - [c20]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete
Unlearning Scanner Bias for MRI Harmonisation. MICCAI (2) 2020: 369-378 - [c19]Lorenzo Venturini
Uncertainty Estimates as Data Selection Criteria to Boost Omni-Supervised Learning. MICCAI (1) 2020: 689-698 - [c18]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete
Unlearning Scanner Bias for MRI Harmonisation in Medical Image Segmentation. MIUA 2020: 15-25 - [c17]Madeleine K. Wyburd, Mark Jenkinson, Ana I. L. Namburete
Cortical Plate Segmentation Using CNNs in 3D Fetal Ultrasound. MIUA 2020: 56-68 - [c16]Linde S. Hesse
Improving U-Net Segmentation with Active Contour Based Label Correction. MIUA 2020: 69-81 - [c15]Nora Vogt, Michael Brady, Ged Ridgway, John Connell
Segmenting Hepatocellular Carcinoma in Multi-phase CT. MIUA 2020: 82-92 - [e1]Bartlomiej W. Papiez
Medical Image Understanding and Analysis - 24th Annual Conference, MIUA 2020, Oxford, UK, July 15-17, 2020, Proceedings. Communications in Computer and Information Science 1248, Springer 2020, ISBN 978-3-030-52790-7 [contents] - [i3]Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou, J. Alison Noble:
Self-Supervised Ultrasound to MRI Fetal Brain Image Synthesis. CoRR abs/2008.08698 (2020)
2010 – 2019
- 2019
- [c14]Jianbo Jiao
Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images. MLMI@MICCAI 2019: 178-186 - [c13]Nicola K. Dinsdale, Mark Jenkinson, Ana I. L. Namburete
Spatial Warping Network for 3D Segmentation of the Hippocampus in MR Images. MICCAI (3) 2019: 284-291 - [c12]Felipe Moser
Automated Fetal Brain Extraction from Clinical Ultrasound Volumes Using 3D Convolutional Neural Networks. MIUA 2019: 151-163 - [c11]Lorenzo Venturini
Multi-task CNN for Structural Semantic Segmentation in 3D Fetal Brain Ultrasound. MIUA 2019: 164-173 - [i2]Jianbo Jiao, Ana I. L. Namburete, Aris T. Papageorghiou, J. Alison Noble:
Anatomy-Aware Self-supervised Fetal MRI Synthesis from Unpaired Ultrasound Images. CoRR abs/1909.03483 (2019) - [i1]Felipe Moser, Ruobing Huang, Aris T. Papageorghiou, Bartlomiej W. Papiez, Ana I. L. Namburete:
Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networks. CoRR abs/1911.07566 (2019) - 2018
- [j3]Ana I. L. Namburete
Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning. Medical Image Anal. 46: 1-14 (2018) - [c10]Sagar Vaze, Ana I. L. Namburete
Segmentation of Fetal Adipose Tissue Using Efficient CNNs for Portable Ultrasound. DATRA/PIPPI@MICCAI 2018: 55-65 - [c9]Ana I. L. Namburete
Multi-channel Groupwise Registration to Construct an Ultrasound-Specific Fetal Brain Atlas. DATRA/PIPPI@MICCAI 2018: 76-86 - [c8]Ruobing Huang, J. Alison Noble
Omni-Supervised Learning: Scaling Up to Large Unlabelled Medical Datasets. MICCAI (1) 2018: 572-580 - 2017
- [c7]Ana I. L. Namburete
Robust Regression of Brain Maturation from 3D Fetal Neurosonography Using CRNs. FIFI/OMIA@MICCAI 2017: 73-80 - 2015
- [j2]Richard V. Stebbing, Ana I. L. Namburete
Data-driven shape parameterization for segmentation of the right ventricle from 3D+t echocardiography. Medical Image Anal. 21(1): 29-39 (2015) - [j1]Ana I. L. Namburete
Learning-based prediction of gestational age from ultrasound images of the fetal brain. Medical Image Anal. 21(1): 72-86 (2015) - [c6]Ruobing Huang, Ana I. L. Namburete, Mohammad Yaqub, J. Alison Noble:
Automated Mid-sagittal Plane Selection for Corpus Callosum Visualization in 3D Ultrasound Images. MIUA 2015: 46-51 - 2014
- [c5]Ana Ineyda Luisa Namburete
Predicting Fetal Neurodevelopmental Age from Ultrasound Images. MICCAI (2) 2014: 260-267 - [c4]Ana I. L. Namburete, Richard V. Stebbing, J. Alison Noble:
Diagnostic Plane Extraction from 3D Parametric Surface of the Fetal Cranium. MIUA 2014: 27-32 - 2013
- [c3]Ana Ineyda Luisa Namburete
Fetal cranial segmentation in 2D ultrasound images using shape properties of pixel clusters. ISBI 2013: 720-723 - 2012
- [c2]Glenn H. Chapman, Jenny Leung, Rohit Thomas, Ana I. L. Namburete
Projecting the rate of in-field pixel defects based on pixel size, sensor area, and ISO. Sensors, Cameras, and Systems for Industrial and Scientific Applications 2012: 82980E - 2011
- [c1]Glenn H. Chapman, Jenny Leung, Ana I. L. Namburete
Predicting Pixel Defect Rates Based on Image Sensor Parameters. DFT 2011: 408-416
Coauthor Index
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last updated on 2024-12-10 20:51 CET by the dblp team
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