Nuclear Segmentation
11 papers with code • 1 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Nuclear Segmentation
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
CoNSeP
2018 Data Science Bowl
Cell
MoNuSAC
Latest papers
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
tissueimageanalytics/conic
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Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome.
SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular Layouts
srijay-lab/synclay-framework
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Tissue image generation based on bespoke cellular layouts through the proposed framework allows users to generate different histological patterns from arbitrary topological arrangement of different types of cells.
Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting
lihaoliu-cambridge/simultaneous_semantic_and_instance_segmentation
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In this work, we present a solution framed as a simultaneous semantic and instance segmentation framework.
SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology Images
QuIIL/Sonnet
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IEEE Journal of Biomedical and Health Informatics 2022
We show that the proposed network achieves the state-of-the-art performance in both nuclei segmentation and classification in comparison to several methods that are recently developed for segmentation and/or classification.
RDCNet: Instance segmentation with a minimalist recurrent residual network
fmi-basel/RDCNet
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Instance segmentation is a key step for quantitative microscopy.
Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology Images
Histology images are inherently symmetric under rotation, where each orientation is equally as likely to appear.
Nuclei Segmentation via a Deep Panoptic Model with Semantic Feature Fusion
dliu5812/PFFNet
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International Joint Conference on Artificial Intelligence (IJCAI-19) 2019
Automated detection and segmentation of individual nuclei in histopathology images is important for cancer diagnosis and prognosis.
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images
vqdang/hover_net
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Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow.
Mask R-CNN
tensorflow/models
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ICCV 2017
Our approach efficiently detects objects in an image while simultaneously generating a high-quality segmentation mask for each instance.
Image-to-Image Translation with Conditional Adversarial Networks
tensorflow/models
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CVPR 2017
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.
