Nuclear Segmentation
10 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
Most implemented papers
Image-to-Image Translation with Conditional Adversarial Networks
phillipi/pix2pix
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CVPR 2017
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.
Mask R-CNN
matterport/Mask_RCNN
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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.
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
We consider image transformation problems, where an input image is transformed into an output image.
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images
vqdang/xy_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.
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.
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.
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.
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.
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.
