CytoGAN: Generative Modeling of Cell Images

No abstract is available for this paper.

• Publication year

  2017

• Venue

  bioRxiv

• Publication date

  2017-12-02

• Fields of study

  Biology, Computer Science

• Identifiers
  DOI 10.1101/227645
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• GENERATIVE ADVERSARIAL NETS

  2018cited by this paper
• Wasserstein GAN

  2017cited by this paper
• Improving Phenotypic Measurements in High-Content Imaging Screens

  2017cited by this paper
• Data-analysis strategies for image-based cell profiling

  2017cited by this paper
• Wasserstein Generative Adversarial Networks

  2017cited by this paper
• Generative Modeling with Conditional Autoencoders: Building an Integrated Cell

  2017cited by this paper
• GANs for Biological Image Synthesis

  2017cited by this paper
• Least Squares Generative Adversarial Networks

  2016influential reference
• Applications in image-based profiling of perturbations.

  2016cited by this paper
• Automating Morphological Profiling with Generic Deep Convolutional Networks

  2016influential reference
• Adversarial Feature Learning

  2016cited by this paper
• High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

  2016cited by this paper
• Deep Autoencoders for Dimensionality Reduction of High-Content Screening Data

  2015cited by this paper
• Classifying and segmenting microscopy images with deep multiple instance learning

  2015cited by this paper
• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

  2015influential reference
• Pipeline for illumination correction of images for high-throughput microscopy

  2014cited by this paper
• Comparison of Methods for Image-Based Profiling of Cellular Morphological Responses to Small-Molecule Treatment

  2013cited by this paper
• Annotated high-throughput microscopy image sets for validation

  2012cited by this paper
• CellProfiler: image analysis software for identifying and quantifying cell phenotypes

  2006cited by this paper

• Advancing antibiotic discovery with bacterial cytological profiling: a high-throughput solution to antimicrobial resistance

  2025cites this paper
• High-Quality Synthetic Annotated Tissue Data Using Conditional Generative Adversarial Networks

  2025cites this paper
• Revisiting Deep Archetypal Analysis for Phenotype Discovery in High Content Imaging

  2025cites this paper
• Morphological profiling for drug discovery in the era of deep learning

  2024cites this paper
• Novel Neural Style Transfer based data synthesis method for phase-contrast wound healing assay images

  2024cites this paper
• Decoding phenotypic screening: A comparative analysis of image representations

  2024cites this paper
• Deep learning methods for high-resolution microscale light field image reconstruction: a survey

  2024cites this paper
• A diffusion model conditioned on compound bioactivity profiles for predicting high-content images

  2024cites this paper
• Generative modeling of living cells with SO(3)-equivariant implicit neural representations

  2023cites this paper
• Morphological Profiling for Drug Discovery in the Era of Deep Learning

  2023influential citation
• Virtual staining for pixel-wise and quantitative analysis of single cell images

  2023cites this paper
• High throughput microscopy and single cell phenotypic image-based analysis in toxicology and drug discovery.

  2023cites this paper
• CP2Image: Generating high-quality single-cell images using CellProfiler representations

  2023cites this paper
• Virtual perturbations to assess explainability of deep-learning based cell fate predictors

  2023cites this paper
• Preventative studies should begin now for detecting AI-generated microscopy images

  2023cites this paper
• Out of Distribution Generalization via Interventional Style Transfer in Single-Cell Microscopy

  2023cites this paper
• Unpaired mesh-to-image translation for 3D fluorescent microscopy images of neurons

  2023cites this paper
• Self-supervised learning for analysis of temporal and morphological drug effects in cancer cell imaging data

  2022cites this paper
• Using conditional Generative Adversarial Networks (GAN) to generate de novo synthetic cell nuclei for training machine learning-based image segmentation

  2022cites this paper
• Towards Learned Simulators for Cell Migration

  2022cites this paper
• Comparing representations of biological data learned with different AI paradigms, augmenting and cropping strategies

  2022cites this paper
• Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak Labels

  2022cites this paper
• Deep Learning in Cell Image Analysis

  2022cites this paper
• Using Simulated Training Data of Voxel-Level Generative Models to Improve 3D Neuron Reconstruction

  2022cites this paper
• Weakly-Supervised Cell Classification for Effective High Content Screening

  2022cites this paper
• Classification of cellular states for high-speed image-based microfluidic cell sorting

  2022cites this paper
• CardioVinci: building blocks for virtual cardiac cells using deep learning

  2022cites this paper
• Predicting drug polypharmacology from cell morphology readouts using variational autoencoder latent space arithmetic

  2021cites this paper
• Latent representation learning in biology and translational medicine

  2021cites this paper
• Contrastive Learning of Single-Cell Phenotypic Representations for Treatment Classification

  2021cites this paper
• Toward deep biophysical cytometry: prospects and challenges.

  2021cites this paper
• Image-based cell phenotyping with deep learning.

  2021cites this paper
• A deep generative model of 3D single-cell organization

  2021cites this paper
• A Deep Learning Approach to Capture the Essence of Candida albicans Morphologies

  2021cites this paper
• Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy

  2021cites this paper
• Exploiting generative self-supervised learning for the assessment of biological images with lack of annotations

  2021cites this paper
• A Review of Generative Adversarial Networks (GANs) and Its Applications in a Wide Variety of Disciplines: From Medical to Remote Sensing

  2021cites this paper
• Generative Adversarial Networks for Morphological–Temporal Classification of Stem Cell Images

  2021cites this paper
• Simulation of biomaterials research experiments with generative models

  2021cites this paper
• Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging

  2021cites this paper
• Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis

  2021cites this paper
• CardioVinci: building blocks for virtual cardiac cells using deep learning

  2021cites this paper
• Generative Adversarial Network for Image Synthesis

  2020cites this paper
• Cellcyclegan: Spatiotemporal Microscopy Image Synthesis Of Cell Populations Using Statistical Shape Models And Conditional Gans

  2020cites this paper
• High-content image generation for drug discovery using generative adversarial networks

  2020cites this paper
• Enhancing scientific discoveries in molecular biology with deep generative models

  2020cites this paper
• Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology

  2020cites this paper
• Improved Conditional Flow Models for Molecule to Image Synthesis

  2020cites this paper
• Information system for segmentation of nanoparticles in STM-images

  2020cites this paper
• An overview of biological data generation using generative adversarial networks

  2020cites this paper
• When Deep Learning Meets Cell Image Synthesis

  2019cites this paper
• Towards Annotation-Free Segmentation of Fluorescently Labeled Cell Membranes in Confocal Microscopy Images

  2019cites this paper
• On Generative Modeling of Cell Shape Using 3D GANs

  2019cites this paper
• A Curvature-Enhanced Random Walker Segmentation Method for Detailed Capture of 3D Cell Surface Membranes

  2019cites this paper
• From observing to predicting single-cell structure and function with high-throughput/high-content microscopy

  2019cites this paper
• Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis

  2019cites this paper
• Variational autoencoding tissue response to microenvironment perturbation

  2019cites this paper
• Feedback GAN for DNA optimizes protein functions

  2019cites this paper
• Generative Adversarial Networks for Augmenting Training Data of Microscopic Cell Images

  2019cites this paper
• Phenotypic Image Analysis Software Tools for Exploring and Understanding Big Image Data from Cell-Based Assays.

  2018cites this paper
• Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning

  2018cites this paper
• Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions

  2018cites this paper
• Weakly Supervised Learning of Single-Cell Feature Embeddings

  2018cites this paper
• Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction

  2018cites this paper
• Opportunities and obstacles for deep learning in biology and medicine

  2017cites this paper
• Building a 3D Integrated Cell

  2017cites this paper
• Using Generative Adversarial Networks to create multi-channel images of cells undergoing macropinocytosis

  year unknowncites this paper
• Using SSRL Models to Classify T-cell Autofluorescent Images

  year unknowncites this paper
• Analysis of cellular phenotypes with unbiased image-based generative models

  year unknowncites this paper