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 2650 of 178 papers

TitleStatusHype
TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classificationCode1
Search for temporal cell segmentation robustness in phase-contrast microscopy videosCode1
Training a deep learning model for single-cell segmentation without manual annotationCode1
LIVECell—A large-scale dataset for label-free live cell segmentationCode1
PolarMask++: Enhanced Polar Representation for Single-Shot Instance Segmentation and BeyondCode1
Robust 3D Cell Segmentation: Extending the View of CellposeCode1
Contour Proposal Networks for Biomedical Instance SegmentationCode1
Red Blood Cell Segmentation with Overlapping Cell Separation and Classification on Imbalanced DatasetCode1
Attention-Based Transformers for Instance Segmentation of Cells in MicrostructuresCode1
Local Label Point Correction for Edge Detection of Overlapping Cervical CellsCode1
Accurate and versatile 3D segmentation of plant tissues at cellular resolutionCode1
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and trackingCode1
Few-Shot Microscopy Image Cell SegmentationCode1
Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with ConsistencyCode1
Fully Unsupervised Diversity Denoising with Convolutional Variational AutoencodersCode1
DoubleU-Net: A Deep Convolutional Neural Network for Medical Image SegmentationCode1
Instance Segmentation of Biomedical Images with an Object-aware Embedding Learned with Local ConstraintsCode1
Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape FeaturesCode1
Weakly Supervised Cell Instance Segmentation by Propagating from Detection ResponseCode1
PixCell: A generative foundation model for digital histopathology images0
Moment kernels: a simple and scalable approach for equivariance to rotations and reflections in deep convolutional networks0
Unsupervised cell segmentation by fast Gaussian ProcessesCode0
Reinforced Correlation Between Vision and Language for Precise Medical AI Assistant0
Hybrid Dense-UNet201 Optimization for Pap Smear Image Segmentation Using Spider Monkey Optimization0
Prompting Vision-Language Model for Nuclei Instance Segmentation and ClassificationCode0
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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