mlsanityData to 7 Oct 2026

A Review on Deep-Learning Algorithms for Fetal Ultrasound-Image Analysis

arXiv 2201.12260 ↗First posted 28 Jan 2022eess.IV cs.CV cs.LGcited by 29

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Abstract (arXiv)

Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US) fetal images. Despite a large number of survey papers already present in this field, most of them are focusing on a broader area of medical-image analysis or not covering all fetal US DL applications. This paper surveys the most recent work in the field, with a total of 145 research papers published after 2017. Each paper is analyzed and commented on from both the methodology and application perspective. We categorized the papers in (i) fetal standard-plane detection, (ii) anatomical-structure analysis, and (iii) biometry parameter estimation. For each category, main limitations and open issues are presented. Summary tables are included to facilitate the comparison among the different approaches. Publicly-available datasets and performance metrics commonly used to assess algorithm performance are summarized, too. This paper ends with a critical summary of the current state of the art on DL algorithms for fetal US image analysis and a discussion on current challenges that have to be tackled by researchers working in the field to translate the research methodology into the actual clinical practice.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 43 of its 196 references that are in the map. First posted on arXiv 28 Jan 2022.

Builds on

43 of 196 references.

References · 43

  1. 2016Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localizationcited by 6,690
  2. 2018Attention Gated Networks: Learning to Leverage Salient Regions in Medical Imagescited by 271
  3. 2016What do different evaluation metrics tell us about saliency models?cited by 184
  4. 2016SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasoundcited by 71
  5. 2016Human pose estimation via Convolutional Part Heatmap Regressioncited by 51
  6. 2019Deep learning in ultrasound imagingcited by 38
  7. 2020High-level Prior-based Loss Functions for Medical Image Segmentation: A Surveycited by 28
  8. 2018Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Reviewcited by 19
  9. 2018Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networkscited by 16
  10. 2017Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networkscited by 15
  11. 2018Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Networkcited by 15
  12. 2020Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imagingcited by 15
31 more
  1. 2021A survey on shape-constraint deep learning for medical image segmentationcited by 15
  2. 2021Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstructioncited by 14
  3. 2019Fetal Ultrasound Image Segmentation for Measuring Biometric Parameters Using Multi-Task Deep Learningcited by 13
  4. 2019Agent with Warm Start and Active Termination for Plane Localization in 3D Ultrasoundcited by 13
  5. 2021AutoFB: Automating Fetal Biometry Estimation from Standard Ultrasound Planescited by 13
  6. 2021FetalNet: Multi-task Deep Learning Framework for Fetal Ultrasound Biometric Measurementscited by 13
  7. 2017Temporal HeartNet: Towards Human-Level Automatic Analysis of Fetal Cardiac Screening Videocited by 10
  8. 2018Less is More: Simultaneous View Classification and Landmark Detection for Abdominal Ultrasound Imagescited by 10
  9. 2019Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographerscited by 10
  10. 2020Ultrasound Video Summarization using Deep Reinforcement Learningcited by 10
  11. 2021Agent with Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasoundcited by 10
  12. 2019Estimation of preterm birth markers with U-Net segmentation networkcited by 7
  13. 2021Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasoundcited by 7
  14. 2020Annotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learningcited by 6
  15. 2021Generalize Ultrasound Image Segmentation via Instant and Plug & Play Style Transfercited by 6
  16. 2020Region Proposal Network with Graph Prior and IoU-Balance Loss for Landmark Detection in 3D Ultrasoundcited by 5
  17. 2020Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screeningcited by 5
  18. 2020Spontaneous preterm birth prediction using convolutional neural networkscited by 5
  19. 2020Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignmentcited by 5
  20. 2021Principled Ultrasound Data Augmentation for Classification of Standard Planescited by 5
  21. 2021EllipseNet: Anchor-Free Ellipse Detection for Automatic Cardiac Biometrics in Fetal Echocardiographycited by 5
  22. 2019Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasoundcited by 4
  23. 2019Semi-supervised Learning of Fetal Anatomy from Ultrasoundcited by 4
  24. 2019Localization of Fetal Head in Ultrasound Images by Multiscale View and Deep Neural Networkscited by 4
  25. 2019Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networkscited by 3
  26. 2020Deep Image Translation for Enhancing Simulated Ultrasound Imagescited by 3
  27. 2019FetusMap: Fetal Pose Estimation in 3D Ultrasoundcited by 2
  28. 2020Hybrid Attention for Automatic Segmentation of Whole Fetal Head in Prenatal Ultrasound Volumescited by 2
  29. 2021Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasoundcited by 2
  30. 2019Joint Segmentation and Landmark Localization of Fetal Femur in Ultrasound Volumescited by 1
  31. 2021A Dual Adversarial Calibration Framework for Automatic Fetal Brain Biometrycited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 6; 2025: 9; 2026: 10.

29 papers.

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  1. 2024PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Imagescited by 8
  2. 2023Towards Realistic Ultrasound Fetal Brain Imaging Synthesiscited by 5
  3. 2023Multi-Task Learning Approach for Unified Biometric Estimation from Fetal Ultrasound Anomaly Scanscited by 4
  4. 2025FetalFlex: Anatomy-Guided Diffusion Model for Flexible Control on Fetal Ultrasound Image Synthesiscited by 4
  5. 2024Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasoundcited by 3
  6. 2024Generative Diffusion Model Bootstraps Zero-shot Classification of Fetal Ultrasound Images In Underrepresented African Populationscited by 3
  7. 2024Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound imagescited by 2
  8. 2025DSSAU-Net:U-Shaped Hybrid Network for Pubic Symphysis and Fetal Head Segmentationcited by 2
  9. 2025A multi-centre, multi-device benchmark dataset for landmark-based comprehensive fetal biometrycited by 2
  10. 2022Empirical Study of Quality Image Assessment for Synthesis of Fetal Head Ultrasound Imaging with DCGANscited by 1
  11. 2025Epistemic-aware Vision-Language Foundation Model for Fetal Ultrasound Interpretationcited by 1
  12. 2025Challenging DINOv3 Foundation Model under Low Inter-Class Variability: A Case Study on Fetal Brain Ultrasoundcited by 1
17 more
  1. 2026FUGC: Benchmarking Semi-Supervised Learning Methods for Cervical Segmentationcited by 1
  2. 2026Beyond Benchmarks of IUGC: Rethinking Requirements of Deep Learning Methods for Intrapartum Ultrasound Biometry from Fetal Ultrasound Videoscited by 1
  3. 2023A Federated Learning Framework for Stenosis Detectioncited by 0
  4. 2024Leveraging Self-Supervised Learning for Fetal Cardiac Planes Classification using Ultrasound Scan Videoscited by 0
  5. 2024U-WNO:U-Net-enhanced Wavelet Neural Operator for fetal head segmentationcited by 0
  6. 2025Biologically Inspired Deep Learning Approaches for Fetal Ultrasound Image Classificationcited by 0
  7. 2025Fusing Radiomic Features with Deep Representations for Gestational Age Estimation in Fetal Ultrasound Imagescited by 0
  8. 2025Multi-Contrast Fusion Module: An attention mechanism integrating multi-contrast features for fetal torso plane classificationcited by 0
  9. 2025Diagnostic Performance of Universal-Learning Ultrasound AI Across Multiple Organs and Tasks: the UUSIC25 Challengecited by 0
  10. 2026Uncertainty-Calibrated Explainable Artificial Intelligence for Fetal Ultrasound Plane Classification: A Systematic Reviewcited by 0
  11. 2026FetalAgents: A Multi-Agent System for Fetal Ultrasound Image and Video Analysiscited by 0
  12. 2026Domain-Guided YOLO26 with Composite BCE-Dice-Lov'asz Loss for Multi-Class Fetal Head Ultrasound Segmentationcited by 0
  13. 2026Towards Reliable Fetal Ultrasound Interpretation with Multi-Agent Collaborationcited by 0
  14. 2026A Clinician-Centered Pipeline for Annotation and Evaluation in Ultrasound AI Studiescited by 0
  15. 2026FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Imagescited by 0
  16. 2026FUSEP: A Multi-Center Benchmark for Diverse Tasks in Early Pregnancy Fetal Ultrasound Screeningcited by 0
  17. 2026Towards Whole-Study Screening for Congenital Heart Disease in Fetal Ultrasound Using Multiple Instance Learningcited by 0