SOTAVerified

Cell Segmentation

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

Papers

Showing 125 of 178 papers

TitleStatusHype
Deep Learning in Single-Cell AnalysisCode3
U-Net: Convolutional Networks for Biomedical Image SegmentationCode3
InstanSeg: an embedding-based instance segmentation algorithm optimized for accurate, efficient and portable cell segmentationCode3
Cell Detection with Star-convex PolygonsCode2
CellViT: Vision Transformers for Precise Cell Segmentation and ClassificationCode2
Omnipose: a high-precision, morphology-independent solution for bacterial cell segmentationCode2
Exploiting Scale-Variant Attention for Segmenting Small Medical ObjectsCode2
U-Mamba: Enhancing Long-range Dependency for Biomedical Image SegmentationCode2
CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation ModelsCode2
LKCell: Efficient Cell Nuclei Instance Segmentation with Large Convolution KernelsCode1
Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local ConstraintsCode1
Local Label Point Correction for Edge Detection of Overlapping Cervical CellsCode1
Large-Scale Multi-Hypotheses Cell Tracking Using Ultrametric Contours MapsCode1
LIVECell—A large-scale dataset for label-free live cell segmentationCode1
ICOS Protein Expression Segmentation: Can Transformer Networks Give Better Results?Code1
MEDIAR: Harmony of Data-Centric and Model-Centric for Multi-Modality MicroscopyCode1
Exploring Unsupervised Cell Recognition with Prior Self-activation MapsCode1
An Instance Segmentation Dataset of Yeast Cells in MicrostructuresCode1
Fully Unsupervised Diversity Denoising with Convolutional Variational AutoencodersCode1
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and trackingCode1
Attention-Based Transformers for Instance Segmentation of Cells in MicrostructuresCode1
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image SegmentationCode1
CellVTA: Enhancing Vision Foundation Models for Accurate Cell Segmentation and ClassificationCode1
HistoSmith: Single-Stage Histology Image-Label Generation via Conditional Latent Diffusion for Enhanced Cell Segmentation and ClassificationCode1
Accurate and versatile 3D segmentation of plant tissues at cellular resolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Dual U-Net (Neighbor distances)SEG (~Mean IoU)0.9Unverified
2DecLSTMSEG (~Mean IoU)0.84Unverified
3EncLSTMSEG (~Mean IoU)0.81Unverified
#ModelMetricClaimedVerifiedStatus
1Cascade Mask RCNN-ResNest-200mask AP47.9Unverified
2CenterMask-VoVNet2-FPNmask AP47.8Unverified
3Point2Maskmask AP43.53Unverified
#ModelMetricClaimedVerifiedStatus
1EncLSTMSEG (~Mean IoU)0.79Unverified
2DecLSTMSEG (~Mean IoU)0.51Unverified
#ModelMetricClaimedVerifiedStatus
1DeepCeNSmask AP52.56Unverified
2EVICAN-MRCNNmask AP32.2Unverified
#ModelMetricClaimedVerifiedStatus
1DecLSTMSEG (~Mean IoU)0.85Unverified
2EncLSTMSEG (~Mean IoU)0.85Unverified
#ModelMetricClaimedVerifiedStatus
1EncLSTMSEG (~Mean IoU)0.81Unverified
2DecLSTMSEG (~Mean IoU)0.8Unverified
#ModelMetricClaimedVerifiedStatus
1PromptNuAverage Dice0.86Unverified
#ModelMetricClaimedVerifiedStatus
1Dual U-Net (Neighbor distances)SEG (~Mean IoU)0.62Unverified
#ModelMetricClaimedVerifiedStatus
1PromptNuAverage Dice0.84Unverified
#ModelMetricClaimedVerifiedStatus
1PromptNuAverage Dice0.86Unverified
#ModelMetricClaimedVerifiedStatus
1EncLSTMSEG (~Mean IoU)0.84Unverified