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Nuclear Segmentation

Papers

Showing 125 of 33 papers

TitleStatusHype
Towards Large-Scale Training of Pathology Foundation ModelsCode2
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and CountingCode1
Image-to-Image Translation with Conditional Adversarial NetworksCode1
Nuclei Segmentation via a Deep Panoptic Model with Semantic Feature FusionCode1
Mask R-CNNCode1
Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology ImagesCode1
Perceptual Losses for Real-Time Style Transfer and Super-ResolutionCode1
SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular LayoutsCode1
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology ImagesCode1
SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology ImagesCode1
Accurate Nuclear Segmentation with Center Vector Encoding0
A Standardized Pipeline for Colon Nuclei Identification and Counting Challenge0
Nuclear Segmentation and Classification: On Color & Compression Generalization0
Nuclei panoptic segmentation and composition regression with multi-task deep neural networks0
NuClick: From Clicks in the Nuclei to Nuclear Boundaries0
Panoptic Segmentation with an End-to-End Cell R-CNN for Pathology Image Analysis0
Separable-HoverNet and Instance-YOLO for Colon Nuclei Identification and Counting0
Nuclear Instance Segmentation using a Proposal-Free Spatially Aware Deep Learning Framework0
A Deep Learning Framework for Nuclear Segmentation and Classification in Histopathological Images0
APSeg: Auto-Prompt Model with Acquired and Injected Knowledge for Nuclear Instance Segmentation and Classification0
Cellular Segmentation and Composition in Routine Histology Images using Deep Learning0
Classification of Tumor Histology via Morphometric Context0
CoNIC: Colon Nuclei Identification and Counting Challenge 20220
Deep Learning Models Delineates Multiple Nuclear Phenotypes in H&E Stained Histology Sections0
GRED: Graph-Regularized 3D Shape Reconstruction from Highly Anisotropic and Noisy Images0
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