Alison Noble
Technikos Professor of Biomedical Engineering
Develops machine learning for medical image analysis, especially fetal and obstetric ultrasound.
Alison Noble's lab at Oxford works on medical imaging & healthcare AI. 96 papers since 2023, 21 at top venues, mostly Medical Image Analysis and ISBI. 8 PhD students. 12 alumni. Applications close .
At a glance
- papers, 2023–2026
- 25/ year
- at T1 venues
- 22%
- PhD students
- 8
- MS students
- 0
- alumni listed
- 12
Papers by yearfrom the lab homepage, 2023–2026
- 19 papers2026 · T1 1 · collecting
- 27 papers2025 · T1 11
- 21 papers2024 · T1 1
- 29 papers2023 · T1 8
T1 venuesOtherVenues: Medical Image Analysis, ISBI, npj Digital Medicine, AAAI, CVPR
Research focuspaper titles that use each topic's words
- ultrasound45 papers
- fetal38 papers
- Medical imaging & healthcare AI6 papers
- image analysis1 paper
- especially0 papers
Paper list
From the lab homepage.
202619 papers
- Frontiers in Public Health“Now that the baby is out, I can be vaccinated”: a qualitative study on COVID-19 vaccine hesitancy in pregnant women in Kilifi, Kenya (opens in a new tab)
- Nature Biomedical EngineeringA visually grounded language model for fetal ultrasound understanding (opens in a new tab)
- BJOGDeterminants of Pre-Eclampsia: Advancing a Conceptual Framework. (opens in a new tab)
- Ultrasound in Obstetrics and GynecologyEP08.07: Clinician vs AI prenatal prediction of the need for balloon atrial septostomy in transposition of the great arteries: multicenter CAIFE study data (opens in a new tab)
- Ultrasound in Obstetrics and GynecologyEP08.31: AI‐driven fetal echocardiography with color Doppler for detection congenital heart defects: data from the international multicenter CAIFE study (opens in a new tab)
- Ultrasound in Obstetrics and GynecologyEP08.32: Fetal echocardiographic biomarkers for prenatal prediction of major congenital heart defects: data from the international multicenter CAIFE study (opens in a new tab)
- Ultrasound in Obstetrics and GynecologyEP08.78: Divergent gestational trends of fetal echocardiographic biomarkers in congenital heart defects: data from the international multicenter CAIFE study (opens in a new tab)
- Information FusionFedExIT - Missing Class-agnostic Semi-Supervised Federated Learning with Extreme Imbalance Tackling Scheme (opens in a new tab)
- npj Digital MedicineHuman-AI Collaboration in Healthcare: A Scoping Review (opens in a new tab)
- —Incidence and risk factors for stillbirth in Kenya, Mozambique and the Gambia: the PRECISE cohort study (opens in a new tab)
- BJOG An International Journal of Obstetrics & GynaecologyIntegrating Social and Clinical Determinants of Pre‐Eclampsia: A Hierarchical Systematic Review and Conceptual Framework for Prevention (opens in a new tab)
- Lecture Notes in Computer ScienceLatent Motion Profiling for Annotation-Free Cardiac Phase Detection in Adult and Fetal Echocardiography Videos (opens in a new tab)
202527 papers
- Computers in biology and medicineA comprehensive scoping review on machine learning-based fetal echocardiography analysis. (opens in a new tab)
- —A Deep Learning Framework for Fetal Heart Tracking in Ultrasound Videos: Toward Enhanced Congenital Heart Defects Detection (opens in a new tab)
- MICCAI Meets Africa Workshop @ MICCAIAn automated pipeline for the identification of liver tissue in ultrasound video (opens in a new tab)
- Mayo Clinic Proceedings: Digital HealthArtificial Intelligence Image-Diagnosis for Female Genital Schistosomiasis (opens in a new tab)
- EClinicalMedicineArtificial intelligence-enabled prenatal ultrasound for the detection of fetal cardiac abnormalities: a systematic review and meta-analysis (opens in a new tab)
- NeurIPS (T1)DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging (opens in a new tab)
- TMLR (T1)Explaining Explainability: Recommendations for Effective Use of Concept Activation Vectors
- CVPR (T1)F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics (opens in a new tab)
- WACVFeasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities (opens in a new tab)
- —Fetal Ultrasound Video Representation Learning Using Contrastive Rubik’s Cube Recovery (opens in a new tab)
- Medical Image Analysis (T1)HarmonicEchoNet: Leveraging harmonic convolutions for automated standard plane detection in fetal heart ultrasound videos (opens in a new tab)
- Medical Image Analysis (T1)IterMask3D: Unsupervised anomaly detection and segmentation with test-time iterative mask refinement in 3D brain MRI (opens in a new tab)
202421 papers
- 339-348$$\mathrm {IterMask^2}$$: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI (opens in a new tab)
- British Journal of AnaesthesiaArtificial intelligence for ultrasound scanning in regional anaesthesia: a scoping review of the evidence from multiple disciplines (opens in a new tab)
- British Journal of AnaesthesiaAssistive artificial intelligence for enhanced patient access to ultrasound-guided regional anaesthesia (opens in a new tab)
- Scientific ReportsAudio-visual modelling in a clinical setting (opens in a new tab)
- Ultrasound in Medicine and BiologyAutomating the human action of first-trimester biometry measurement from real-world freehand ultrasound (opens in a new tab)
- WFUMB Ultrasound OpenDetection of fetal congenital heart defects on three-vessel view ultrasound videos (opens in a new tab)
- Frontiers in Global Women's HealthDiagnostic accuracy of a non-invasive spot-check hemoglobin meter, Masimo Rad-67® pulse CO-Oximeter®, in detection of anemia in antenatal care settings in Kenya (opens in a new tab)
- ISBIDual Representation Learning From Fetal Ultrasound Video and Sonographer Audio (opens in a new tab)
- Ultrasound in Obstetrics and GynecologyEP01.34: Towards AI‐enabled navigation of the second trimester anomaly scan (opens in a new tab)
- —IterMask2: Iterative Unsupervised Anomaly Segmentation via Spatial and Frequency Masking for Brain Lesions in MRI (opens in a new tab)
- —MMSummary: Multimodal Summary Generation for Fetal Ultrasound Video (opens in a new tab)
- —Neuron Segmentation from Noisy Fluorescence Microscopy Images Using Deep Learning with Local and Global Scale Fusion (opens in a new tab)
202329 papers
- Lecture Notes in Computer ScienceA Kernel Density Estimation Based Quality Metric for Quality Assessment of Obstetric Ultrasound Video (opens in a new tab)
- TMI (T1)A Machine Learning Method for Automated Description and Workflow Analysis of First Trimester Ultrasound Scans. (opens in a new tab)
- Mayo Clinic Proceedings Digital HealthA Review of Computer-Aided Diagnostic Algorithms for Cervical Neoplasia and an Assessment of Their Applicability to Female Genital Schistosomiasis (opens in a new tab)
- Lancet HaematologyAssociation between maternal haemoglobin concentrations and maternal and neonatal outcomes: the prospective, observational, multinational, INTERBIO-21st fetal study (opens in a new tab)
- ISBIAutomated description and workflow analysis of fetal echocardiography in first-trimester ultrasound video scans (opens in a new tab)
- ISBICNSEG-GAN: a lightweight generative adversarial network for segmentation of CRL and NT from first-trimester fetal ultrasound (opens in a new tab)
- IEEE transactions on ultrasonics, ferroelectrics, and frequency controlCOMFormer: Classification of Maternal-Fetal and Brain Anatomy Using a Residual Cross-Covariance Attention Guided Transformer in Ultrasound. (opens in a new tab)
- ISBID2ANET: Densely Attentional-Aware Network for first trimester ultrasound CRL and NT segmentation (opens in a new tab)
- MICCAI (T1)Dual conditioned diffusion models for out-of-distribution detection: application to fetal ultrasound videos (opens in a new tab)
- Ultrasound in Obstetrics and GynecologyEP02.46: An AI system (SonoLyst) achieves expert level performance when categorising images for adherence to ISUOG mid‐trimester screening guidelines (opens in a new tab)
- Ultrasound in Obstetrics and GynecologyEP07.16: Visibility of fetal brain structures in blind ultrasound sweeps (opens in a new tab)
- Medical Image Analysis (T1)Gaze-probe joint guidance with multi-task learning in obstetric ultrasound scanning. (opens in a new tab)
Where alumni went12 listed
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
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- English
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- Fee
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Not yet confirmed for this intake.
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