Browse State-of-the-Art › Cell Segmentation
Cell Segmentation
91 papers with code · 12 benchmarks · 22 datasets archive 2025-07-28
Cell Segmentation is a task of splitting a microscopic image domain into segments, which represent individual instances of cells. It is a fundamental step in many biomedical studies, and it is regarded as a cornerstone of image-based cellular research. Cellular morphology is an indicator of a physiological state of the cell, and a well-segmented image can capture biologically relevant morphological information.
Source: Cell Segmentation by Combining Marker-controlled Watershed and Deep Learning
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
12 leaderboard tables shown for this task, 12 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 12 until expanded.
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
22 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
30 shown of 91 papers with code (178 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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18 May 2015 487 repositories listed Syntology ran 510 of 757 samples · 247 unverified · 426 pointer-only (licence)There is large consent that successful training of deep networks requires many thousand annotated training samples.
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23 Aug 2023 6 repositories listedCompared to the segment anything model, SPPNet shows roughly 20 times faster inference, with 1/70 parameters and computational cost.
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22 Oct 2022 6 repositories listed Syntology ran 1 of 4 samples · 3 unverified · 1 pointer-only (licence)Under each task, we describe the most recent developments in classical and deep learning methods and discuss their advantages and disadvantages.
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8 Jun 2020 4 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 5 pointer-only (licence)The encouraging results, produced on various medical image segmentation datasets, show that DoubleU-Net can be used as a strong baseline for both medical image segmentation and cross-dataset evaluation testing to…
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27 Jun 2023 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications.
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23 Jun 2020 3 repositories listedSegmentation is a fundamental process in microscopic cell image analysis.
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10 Jun 2020 3 repositories listedDeep Learning based methods have emerged as the indisputable leaders for virtually all image restoration tasks.
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7 Mar 2019 3 repositories listedIn this paper, we propose a context encoder network (referred to as CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation.
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9 Jun 2018 3 repositories listed Syntology ran 1 of 33 samples · 32 unverified · 2 pointer-only (licence)Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications.
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29 May 2018 3 repositories listedLive cell microscopy sequences exhibit complex spatial structures and complicated temporal behaviour, making their analysis a challenging task.
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20 Apr 2023 2 repositories listedThis strategy achieves self-learning by sharing knowledge between a principal model and a very light-weight collaborator model.
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7 Dec 2022 2 repositories listed Syntology ran 4 of 11 samples · 7 unverifiedCell segmentation is a fundamental task for computational biology analysis.
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14 Dec 2021 2 repositories listedGenerating training data is expensive and a major hindrance in the wider adoption of machine learning based methods for cell segmentation.
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7 Apr 2021 2 repositories listedWe construct CPN models with different backbone networks, and apply them to instance segmentation of cells in datasets from different modalities.
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21 Apr 2020 2 repositories listedThe network is trained to output embedding vectors of similar directions for pixels from the same object, while adjacent objects are orthogonal in the embedding space, which effectively avoids the fusion of objects in a…
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25 Apr 2018 2 repositories listedDeep learning based models have had great success in object detection, but the state of the art models have not yet been widely applied to biological image data.
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24 May 2025 1 repository listedCell boundary information is crucial for analyzing cell behaviors from time-lapse microscopy videos.
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1 Apr 2025 1 repository listedTo address this problem, we propose CellVTA (Cell Vision Transformer with Adapter), a novel method that improves the performance of vision foundation models for cell instance segmentation by incorporating a CNN-based…
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27 Mar 2025 1 repository listedNuclei instance segmentation and classification are a fundamental and challenging task in whole slide Imaging (WSI) analysis.
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14 Mar 2025 1 repository listedCell instance segmentation (CIS) is crucial for identifying individual cell morphologies in histopathological images, providing valuable insights for biological and medical research.
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12 Feb 2025 1 repository listedExperimental results demonstrate improvements in cell instance segmentation and classification, particularly for underrepresented cell types like neutrophils in the Conic dataset.
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11 Feb 2025 1 repository listedThe Consensus Matrix defines regions where both the AI and annotators agree on cell and non-cell annotations, which are prioritized with stronger supervision.
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8 Feb 2025 1 repository listedThis study introduces SEFI (SEgmentation-Free Integration), a novel method for integrating morphological features of cell nuclei with spatial transcriptomics data.
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4 Feb 2025 1 repository listedThis study investigates the representation learning gap between these two categories by analyzing multi-level patch embeddings applied to cell instance segmentation and classification.
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31 Jan 2025 1 repository listedEpithelial cells form diverse structures from squamous spherical organoids to densely packed pseudostratified tissues.
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9 Jan 2025 1 repository listedDigital Pathology is a cornerstone in the diagnosis and treatment of diseases.
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2 Dec 2024 1 repository listedWe introduce CellSeg1, a practical solution for segmenting cells of arbitrary morphology and modality with a few dozen cell annotations in 1 image.
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18 Nov 2024 1 repository listedTo overcome this, we propose a novel framework for synthesizing densely annotated 2D and 3D cell microscopy images using cascaded diffusion models.
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24 Oct 2024 1 repository listedAdvanced image segmentation and processing tools present an opportunity to study cell processes and their dynamics.
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18 Oct 2024 1 repository listedTo address these issues, we propose a novel framework called RA-SE-ASPP-Net, which incorporates Residual Blocks, Attention Mechanism, Squeeze-and-Excitation connection, and Atrous Spatial Pyramid Pooling to achieve…
Syntology lines on 6 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections