Nuclear Segmentation

10 papers with code • 1 benchmarks • 4 datasets

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Most implemented papers

Image-to-Image Translation with Conditional Adversarial Networks

phillipi/pix2pix CVPR 2017

We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.

Mask R-CNN

matterport/Mask_RCNN 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

alexjc/neural-enhance 27 Mar 2016

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 16 Dec 2018

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

simongraham/dsf-cnn 6 Apr 2020

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 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 2 Oct 2020

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 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 1 Mar 2022

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 28 Dec 2022

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.