Ana Namburete
Associate Professor of Computer Science
Develops deep learning methods for fetal and neonatal neuroimaging, including 3D ultrasound reconstruction, segmentation and atlas construction.
Ana Namburete's lab at Oxford works on neuroscience & brain-computer interfaces, 3D vision & neural rendering and recognition, detection & segmentation. 20 papers since 2023, 6 at top venues, mostly Medical Image Analysis and ISBI. 5 PhD students. 11 alumni. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 30%
- PhD students
- 5
- MS students
- 0
- alumni listed
- 11
Papers by yearfrom the lab homepage, 2023–2026
- 7 papers2026 · T1 3 · collecting
- 3 papers2025 · T1 0
- 5 papers2024 · T1 2
- 5 papers2023 · T1 1
T1 venuesOtherVenues: Medical Image Analysis, ISBI, ICLR, Nature, Nature Communications
Research focuspaper titles that use each topic's words
- Neuroscience & brain-computer interfaces10 papers
- fetal10 papers
- ultrasound8 papers
- Recognition, detection & segmentation4 papers
- 3D vision & neural rendering0 papers
Paper list
From the lab homepage.
20267 papers
- Medical Image Analysis (T1)Beyond benchmarks of IUGC: Rethinking requirements of deep learning method for intrapartum ultrasound biometry from fetal ultrasound videos (opens in a new tab)
- Prenatal DiagnosisClinical Grading of Artificial Intelligence‐Based 3D Fetal Brain Segmentations: A Cross‐Vendor Evaluation of Deep Learning in Fetal Neuroimaging (opens in a new tab)
- Ultrasound in Obstetrics & GynecologyDeep learning assessment of fetal brain maturation on 3D ultrasound volumes in early‐onset fetal growth restriction (opens in a new tab)
- The Lancet Obstetrics, Gynaecology, & Women's HealthImpaired fetal brain growth and neurodevelopmental deficits at 2 years: deep phenotyping of maternal–fetal pathophysiology (opens in a new tab)
- Nature Communications (T1)Normative growth trajectories of fetal brain regions validated by satisfactory maturation of neurodevelopmental domains at 2 years of age (opens in a new tab)
- Lecture Notes in Computer ScienceSemi-supervised 3D Medical Segmentation from 2D Natural Images Pretrained Model (opens in a new tab)
- ICLR (T1)UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumes (opens in a new tab)
20253 papers
- Human Brain MappingCross‐Modality Comparison of Fetal Brain Phenotypes: Insights From Short‐Interval Second‐Trimester MRI and Ultrasound Imaging (opens in a new tab)
- ISBIExploring Test Time Adaptation for Subcortical Segmentation of the Fetal Brain in 3D Ultrasound (opens in a new tab)
- ISBIRapidVol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scans (opens in a new tab)
20245 papers
- Medical Image Analysis (T1)Anatomically plausible segmentations: Explicitly preserving topology through prior deformations (opens in a new tab)
- Lecture Notes in Computer ScienceGeometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos (opens in a new tab)
- openRxivIs Your Style Transfer Doing Anything Useful? An Investigation Into Hippocampus Segmentation and the Role of Preprocessing (opens in a new tab)
- Medical Image Analysis (T1)Sensorless volumetric reconstruction of fetal brain freehand ultrasound scans with deep implicit representation (opens in a new tab)
- openRxivUniFed: A unified deep learning framework for segmentation of partially labelled, distributed neuroimaging data (opens in a new tab)
20235 papers
- Frontiers in BioinformaticsBayesian networks and imaging-derived phenotypes highlight the role of fat deposition in COVID-19 hospitalisation risk (opens in a new tab)
- SDSBrain Ages Derived from Different MRI Modalities are Associated with Distinct Biological Phenotypes (opens in a new tab)
- Nature (T1)Normative spatiotemporal fetal brain maturation with satisfactory development at 2 years (opens in a new tab)
- Frontiers in EndocrinologyPoor glycaemic control and ectopic fat deposition mediates the increased risk of non-alcoholic steatohepatitis in high-risk populations with type 2 diabetes: Insights from Bayesian-network modelling (opens in a new tab)
- ICMHIThe impact of projected increases in obesity prevalence on incident liver disease in the UK: Insights from Bayesian-network modelling (opens in a new tab)
Where alumni went11 listed
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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