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Nuclear Segmentation

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Showing 1–33 of 33 papers

TitleStatusHype
Towards Large-Scale Training of Pathology Foundation ModelsCode2
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and CountingCode1
SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular LayoutsCode1
SONNET: A Self-Guided Ordinal Regression Neural Network for Segmentation and Classification of Nuclei in Large-Scale Multi-Tissue Histology ImagesCode1
Dense Steerable Filter CNNs for Exploiting Rotational Symmetry in Histology ImagesCode1
Nuclei Segmentation via a Deep Panoptic Model with Semantic Feature FusionCode1
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology ImagesCode1
Mask R-CNNCode1
Image-to-Image Translation with Conditional Adversarial NetworksCode1
Perceptual Losses for Real-Time Style Transfer and Super-ResolutionCode1
Unpaired Image-to-Image Translation for Segmentation and Signal Unmixing—0
APSeg: Auto-Prompt Model with Acquired and Injected Knowledge for Nuclear Instance Segmentation and Classification—0
FrGNet: A fourier-guided weakly-supervised framework for nuclear instance segmentationCode0
Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathologyCode0
HoverFast: an accurate, high-throughput, clinically deployable nuclear segmentation tool for brightfield digital pathology images—0
Nuclear Segmentation and Classification: On Color & Compression Generalization—0
Cellular Segmentation and Composition in Routine Histology Images using Deep Learning—0
A Deep Learning Framework for Nuclear Segmentation and Classification in Histopathological Images—0
Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and CountingCode0
A Standardized Pipeline for Colon Nuclei Identification and Counting Challenge—0
Separable-HoverNet and Instance-YOLO for Colon Nuclei Identification and Counting—0
Nuclei panoptic segmentation and composition regression with multi-task deep neural networks—0
CoNIC: Colon Nuclei Identification and Counting Challenge 2022—0
Meta Mask Correction for Nuclei Segmentation in Histopathological Image—0
RDCNet: Instance segmentation with a minimalist recurrent residual networkCode0
Sparse Coding Driven Deep Decision Tree Ensembles for Nuclear Segmentation in Digital Pathology Images—0
NuClick: From Clicks in the Nuclei to Nuclear Boundaries—0
Nuclear Instance Segmentation using a Proposal-Free Spatially Aware Deep Learning Framework—0
Accurate Nuclear Segmentation with Center Vector Encoding—0
Panoptic Segmentation with an End-to-End Cell R-CNN for Pathology Image Analysis—0
Deep Learning Models Delineates Multiple Nuclear Phenotypes in H&E Stained Histology Sections—0
GRED: Graph-Regularized 3D Shape Reconstruction from Highly Anisotropic and Noisy Images—0
Classification of Tumor Histology via Morphometric Context—0
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