mlsanityData to 7 Oct 2026

NeoUNet: Towards accurate colon polyp segmentation and neoplasm detection

arXiv 2107.05023 ↗First posted 11 Jul 2021eess.IV cs.CVcited by 50

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Abstract (arXiv)

Automatic polyp segmentation has proven to be immensely helpful for endoscopy procedures, reducing the missing rate of adenoma detection for endoscopists while increasing efficiency. However, classifying a polyp as being neoplasm or not and segmenting it at the pixel level is still a challenging task for doctors to perform in a limited time. In this work, we propose a fine-grained formulation for the polyp segmentation problem. Our formulation aims to not only segment polyp regions, but also identify those at high risk of malignancy with high accuracy. In addition, we present a UNet-based neural network architecture called NeoUNet, along with a hybrid loss function to solve this problem. Experiments show highly competitive results for NeoUNet on our benchmark dataset compared to existing polyp segmentation models.

Key facts. Cited by 50 papers in the map (data through 7 Oct 2026). Builds on 21 of its 36 references that are in the map. First posted on arXiv 11 Jul 2021.

Builds on

21 of 36 references.

References · 21

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9 more
  1. 2019UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentationcited by 583
  2. 2020PraNet: Parallel Reverse Attention Network for Polyp Segmentationcited by 460
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 9; 2023: 10; 2024: 13; 2025: 10; 2026: 8.

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  1. 2024EMCAD: Efficient Multi-scale Convolutional Attention Decoding for Medical Image Segmentationcited by 64
  2. 2022TGANet: Text-guided attention for improved polyp segmentationcited by 59
  3. 2023Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentationcited by 29
  4. 2022ColonFormer: An Efficient Transformer based Method for Colon Polyp Segmentationcited by 28
  5. 2023Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Modelscited by 28
  6. 2023TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testingcited by 26
  7. 2022TransResU-Net: Transformer based ResU-Net for Real-Time Colonoscopy Polyp Segmentationcited by 19
  8. 2024Is SAM 2 Better than SAM in Medical Image Segmentation?cited by 16
  9. 2023Towards General Purpose Medical AI: Continual Learning Medical Foundation Modelcited by 14
  10. 2024Frontiers in Intelligent Colonoscopycited by 13
  11. 2024ProMamba: Prompt-Mamba for polyp segmentationcited by 12
  12. 2024VLSM-Adapter: Finetuning Vision-Language Segmentation Efficiently with Lightweight Blockscited by 11
38 more
  1. 2022BlazeNeo: Blazing fast polyp segmentation and neoplasm detectioncited by 10
  2. 2025UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretationcited by 10
  3. 2023Attention Mechanisms in Medical Image Segmentation: A Surveycited by 9
  4. 2024PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopycited by 7
  5. 2022DilatedSegNet: A Deep Dilated Segmentation Network for Polyp Segmentationcited by 6
  6. 2022Focal-UNet: UNet-like Focal Modulation for Medical Image Segmentationcited by 6
  7. 2024Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignmentscited by 6
  8. 2024SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy datacited by 6
  9. 2026MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learningcited by 6
  10. 2024Colorectal Polyp Segmentation in the Deep Learning Era: A Comprehensive Surveycited by 5
  11. 2023M3FPolypSegNet: Segmentation Network with Multi-frequency Feature Fusion for Polyp Localization in Colonoscopy Imagescited by 3
  12. 2024TuneVLSeg: Prompt Tuning Benchmark for Vision-Language Segmentation Modelscited by 3
  13. 2025EndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosiscited by 3
  14. 2026MedCLIPSeg: Probabilistic Vision-Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentationcited by 3
  15. 2022LAPFormer: A Light and Accurate Polyp Segmentation Transformercited by 2
  16. 2023RaBiT: An Efficient Transformer using Bidirectional Feature Pyramid Network with Reverse Attention for Colon Polyp Segmentationcited by 2
  17. 2025iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detectioncited by 2
  18. 2025K-Prism: A Knowledge-Guided and Prompt Integrated Universal Medical Image Segmentation Modelcited by 2
  19. 2022Automatic Polyp Segmentation with Multiple Kernel Dilated Convolution Networkcited by 1
  20. 2022Online pseudo labeling for polyp segmentation with momentum networkscited by 1
  21. 2023TransRUPNet for Improved Polyp Segmentationcited by 1
  22. 2023RetSeg: Retention-based Colorectal Polyps Segmentation Networkcited by 1
  23. 2025VLSM-Ensemble: Ensembling CLIP-based Vision-Language Models for Enhanced Medical Image Segmentationcited by 1
  24. 2025RRTS Dataset: A Benchmark Colonoscopy Dataset from Resource-Limited Settings for Computer-Aided Diagnosis Researchcited by 1
  25. 2025SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Trackingcited by 1
  26. 2025Improvise, Adapt, Overcome -- Telescopic Adapters for Efficient Fine-tuning of Vision Language Models in Medical Imagingcited by 1
  27. 2026Multi-Scale Global-Instance Prompt Tuning for Continual Test-time Adaptation in Medical Image Segmentationcited by 1
  28. 2026SPEGC: Continual Test-Time Adaptation via Semantic-Prompt-Enhanced Graph Clustering for Medical Image Segmentationcited by 1
  29. 2023Prototype Learning for Out-of-Distribution Polyp Segmentationcited by 0
  30. 2024Polyp segmentation in colonoscopy images using DeepLabV3++cited by 0
  31. 2024Transformer-Enhanced Iterative Feedback Mechanism for Polyp Segmentationcited by 0
  32. 2024Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentationcited by 0
  33. 2025Cycle Context Verification for In-Context Medical Image Segmentationcited by 0
  34. 2025The Power of Certainty: How Confident Models Lead to Better Segmentationcited by 0
  35. 2026MieDB-100k: A Comprehensive Dataset for Medical Image Editingcited by 0
  36. 2026From Adaptation to Generalization: Adaptive Visual Prompting for Medical Image Segmentationcited by 0
  37. 2026MedSIGHT: Towards Grounded Visual Comprehension in Medical Large Vision-Language Modelscited by 0
  38. 2026MedSegBenchmarker: A Raw-Count-First Framework for Controlled 2D Medical Image Segmentation Benchmarkscited by 0