mlsanityData to 7 Oct 2026

Deep Semantic Segmentation of Natural and Medical Images: A Review

arXiv 1910.07655 ↗First posted 16 Oct 2019cs.CV cs.LG eess.IVcited by 124

Not on the map. Why?

Abstract (arXiv)

The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class. This task is a part of the concept of scene understanding or better explaining the global context of an image. In the medical image analysis domain, image segmentation can be used for image-guided interventions, radiotherapy, or improved radiological diagnostics. In this review, we categorize the leading deep learning-based medical and non-medical image segmentation solutions into six main groups of deep architectural, data synthesis-based, loss function-based, sequenced models, weakly supervised, and multi-task methods and provide a comprehensive review of the contributions in each of these groups. Further, for each group, we analyze each variant of these groups and discuss the limitations of the current approaches and present potential future research directions for semantic image segmentation.

Key facts. Cited by 124 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Oct 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 17; 2022: 24; 2023: 34; 2024: 22; 2025: 23; 2026: 4.

124 papers.

Sort:

By area:

  1. 2022Medical Image Segmentation Review: The success of U-Netcited by 190
  2. 2022PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllerscited by 84
  3. 2022Scene Graph Generation: A Comprehensive Surveycited by 73
  4. 2022Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentationcited by 65
  5. 2021Common Limitations of Image Processing Metrics: A Picture Storycited by 58
  6. 2022Towards a Guideline for Evaluation Metrics in Medical Image Segmentationcited by 58
  7. 2023Understanding metric-related pitfalls in image analysis validationcited by 57
  8. 2021Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentationcited by 56
  9. 2023Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentationcited by 53
  10. 2022Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularizationcited by 50
  11. 2021Convolution-Free Medical Image Segmentation using Transformerscited by 49
  12. 2023CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objectscited by 43
38 more
  1. 2023Loss Functions in the Era of Semantic Segmentation: A Survey and Outlookcited by 33
  2. 2023PhenoBench -- A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domaincited by 31
  3. 2022A Survey on Deep Learning for Skin Lesion Segmentationcited by 22
  4. 2023FECANet: Boosting Few-Shot Semantic Segmentation with Feature-Enhanced Context-Aware Networkcited by 22
  5. 2023From CNN to Transformer: A Review of Medical Image Segmentation Modelscited by 22
  6. 2023A Recent Survey of Vision Transformers for Medical Image Segmentationcited by 22
  7. 2021Medical Image Segmentation with Limited Supervision: A Review of Deep Network Modelscited by 21
  8. 2021Modality specific U-Net variants for biomedical image segmentation: A surveycited by 20
  9. 2021A survey on shape-constraint deep learning for medical image segmentationcited by 15
  10. 2021Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Semantic Segmentationcited by 15
  11. 2023Treasure in Distribution: A Domain Randomization based Multi-Source Domain Generalization for 2D Medical Image Segmentationcited by 14
  12. 2021Uncertainty-Aware Deep Co-training for Semi-supervised Medical Image Segmentationcited by 12
  13. 2023PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretrainingcited by 12
  14. 2024Query-guided Prototype Evolution Network for Few-Shot Segmentationcited by 12
  15. 2024CSWin-UNet: Transformer UNet with Cross-Shaped Windows for Medical Image Segmentationcited by 12
  16. 2024Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Surveycited by 11
  17. 2024SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidancecited by 11
  18. 2023Gradient-Semantic Compensation for Incremental Semantic Segmentationcited by 10
  19. 2024Development of Skip Connection in Deep Neural Networks for Computer Vision and Medical Image Analysis: A Surveycited by 10
  20. 2021A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentationcited by 9
  21. 2023MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasetscited by 9
  22. 2022Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label Diffusioncited by 8
  23. 2022Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inferencecited by 7
  24. 2022Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image Generationcited by 7
  25. 2023Iterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic Segmentationcited by 7
  26. 2024Investigating the Quality of DermaMNIST and Fitzpatrick17k Dermatological Image Datasetscited by 7
  27. 2024Cs2K: Class-specific and Class-shared Knowledge Guidance for Incremental Semantic Segmentationcited by 7
  28. 2023Domain Adaptive Sim-to-Real Segmentation of Oropharyngeal Organs Towards Robot-assisted Intubationcited by 6
  29. 2023Segment Any Events via Weighted Adaptation of Pivotal Tokenscited by 5
  30. 2021Interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfacescited by 4
  31. 2021Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labelscited by 4
  32. 2022Improving Classification Model Performance on Chest X-Rays through Lung Segmentationcited by 4
  33. 2022Automatic Fine-grained Glomerular Lesion Recognition in Kidney Pathologycited by 4
  34. 2022Semantic Segmentation of Fruits on Multi-sensor Fused Data in Natural Orchardscited by 4
  35. 2023Radio astronomical images object detection and segmentation: A benchmark on deep learning methodscited by 4
  36. 2023LSFSL: Leveraging Shape Information in Few-shot Learningcited by 4
  37. 2023DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Imagescited by 4
  38. 2023Classification of White Blood Cells Using Machine and Deep Learning Models: A Systematic Reviewcited by 4

50 most cited of 124 All 124 (JSON)