mlsanityData to 7 Oct 2026

Micro-Net: A unified model for segmentation of various objects in microscopy images

arXiv 1804.08145 ↗First posted 22 Apr 2018cs.CVcited by 56

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Abstract (arXiv)

Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images. We present a convolution neural network (CNN) based deep learning architecture for segmentation of objects in microscopy images. The proposed network can be used to segment cells, nuclei and glands in fluorescence microscopy and histology images after slight tuning of input parameters. The network trains at multiple resolutions of the input image, connects the intermediate layers for better localization and context and generates the output using multi-resolution deconvolution filters. The extra convolutional layers which bypass the max-pooling operation allow the network to train for variable input intensities and object size and make it robust to noisy data. We compare our results on publicly available data sets and show that the proposed network outperforms recent deep learning algorithms.

Key facts. Cited by 56 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Apr 2018.

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Citing papers per year: 2021: 10; 2022: 6; 2023: 13; 2024: 15; 2025: 8; 2026: 4.

56 papers.

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  1. 2023CellViT: Vision Transformers for Precise Cell Segmentation and Classificationcited by 108
  2. 2021Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classificationcited by 89
  3. 2021CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentationcited by 32
  4. 2023DiffMix: Diffusion Model-based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasetscited by 28
  5. 2021Multi-Class Cell Detection Using Spatial Context Representationcited by 24
  6. 2021Instance-based Vision Transformer for Subtyping of Papillary Renal Cell Carcinoma in Histopathological Imagecited by 22
  7. 2023Unleashing the Power of Prompt-driven Nucleus Instance Segmentationcited by 19
  8. 2021TA-Net: Topology-Aware Network for Gland Segmentationcited by 17
  9. 2022Nuclei Segmentation with Point Annotations from Pathology Images via Self-Supervised Learning and Co-Trainingcited by 16
  10. 2022Which Pixel to Annotate: a Label-Efficient Nuclei Segmentation Frameworkcited by 14
  11. 2023Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directionscited by 10
  12. 2021Nuclei Grading of Clear Cell Renal Cell Carcinoma in Histopathological Image by Composite High-Resolution Networkcited by 8
38 more
  1. 2021Simultaneous Nuclear Instance and Layer Segmentation in Oral Epithelial Dysplasiacited by 8
  2. 2021PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and Classificationcited by 8
  3. 2024BoNuS: Boundary Mining for Nuclei Segmentation with Partial Point Labelscited by 8
  4. 2024DAWN: Domain-Adaptive Weakly Supervised Nuclei Segmentation via Cross-Task Interactionscited by 8
  5. 2023Topology-Guided Multi-Class Cell Context Generation for Digital Pathologycited by 7
  6. 2022GradMix for nuclei segmentation and classification in imbalanced pathology image datasetscited by 6
  7. 2023Nucleus-aware Self-supervised Pretraining Using Unpaired Image-to-image Translation for Histopathology Imagescited by 6
  8. 2024Learning to Generalize over Subpartitions for Heterogeneity-aware Domain Adaptive Nuclei Segmentationcited by 6
  9. 2024SEINE: Structure Encoding and Interaction Network for Nuclei Instance Segmentationcited by 6
  10. 2024Boundary-Guided Learning for Gene Expression Prediction in Spatial Transcriptomicscited by 6
  11. 2022WDA-Net: Weakly-Supervised Domain Adaptive Segmentation of Electron Microscopycited by 5
  12. 2024DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Imagescited by 5
  13. 2024Evaluating Cell AI Foundation Models in Kidney Pathology with Human-in-the-Loop Enrichmentcited by 5
  14. 2023Fluorescent Neuronal Cells v2: Multi-Task, Multi-Format Annotations for Deep Learning in Microscopycited by 4
  15. 2023HoVer-UNet: Accelerating HoVerNet with UNet-based multi-class nuclei segmentation via knowledge distillationcited by 4
  16. 2024Weakly-Supervised Cross-Domain Segmentation of Electron Microscopy with Sparse Point Annotationcited by 4
  17. 2024Histopathological Image Classification with Cell Morphology Aware Deep Neural Networkscited by 4
  18. 2023Point-supervised Single-cell Segmentation via Collaborative Knowledge Sharingcited by 3
  19. 2023A Fully Automated and Explainable Algorithm for the Prediction of Malignant Transformation in Oral Epithelial Dysplasiacited by 3
  20. 2023Enhancing Nucleus Segmentation with HARU-Net: A Hybrid Attention Based Residual U-Blocks Networkcited by 3
  21. 2024Few-Shot Learning for Annotation-Efficient Nucleus Instance Segmentationcited by 3
  22. 2024Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentationcited by 3
  23. 2024LKCell: Efficient Cell Nuclei Instance Segmentation with Large Convolution Kernelscited by 3
  24. 2025The Four Color Theorem for Cell Instance Segmentationcited by 3
  25. 2025Co-Seg++: Mutual Prompt-Guided Collaborative Learning for Versatile Medical Segmentationcited by 3
  26. 2026MLLM-HWSI: A Multimodal Large Language Model for Hierarchical Whole Slide Image Understandingcited by 3
  27. 2024NuLite -- Lightweight and Fast Model for Nuclei Instance Segmentation and Classificationcited by 2
  28. 2021Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Imagescited by 1
  29. 2022MRL: Learning to Mix with Attention and Convolutionscited by 1
  30. 2025Cell Nuclei Detection and Classification in Whole Slide Images with Transformerscited by 1
  31. 2025AMA-SAM: Adversarial Multi-Domain Alignment of Segment Anything Model for High-Fidelity Histology Nuclei Segmentationcited by 1
  32. 2025IAUNet: Instance-Aware U-Netcited by 1
  33. 2021A Multi-Scale Conditional Deep Model for Tumor Cell Ratio Countingcited by 0
  34. 2022Machine Learning Applications in Lung Cancer Diagnosis, Treatment and Prognosiscited by 0
  35. 2023A three in one bottom-up framework for simultaneous semantic segmentation, instance segmentation and classification of multi-organ nuclei in digital cancer histologycited by 0
  36. 2023DFGET: Displacement-Field Assisted Graph Energy Transmitter for Gland Instance Segmentationcited by 0
  37. 2024A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attentioncited by 0
  38. 2024Whole Slide Image Classification of Salivary Gland Tumourscited by 0

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