Cell Image Analysis Techniques

A semi-automated pipeline for morphological analysis of myonuclei along single muscle fibers

The paper develops a semi-automated image-analysis pipeline to quantify myonuclear morphology and spatial organization in skeletal muscle fibers, improving efficiency and reducing bias.

CellColoc: A modular, open-source workflow for cell colocalization, segmentation, and feature extraction in microscopy images

SynAPSeg: A novel dataset and image analysis framework for deep learning-based synapse detection and quantification

SynAPSeg provides a framework and dataset for deep learning-based synapse detection and quantification, achieving expert-level performance and revealing age-related synaptic changes.

UDIST: unsupervised disentanglement of shape and texture for multi-scale phenotypic profiling in 2D microscopy

UDIST separates shape and texture in microscopy images into independent latent subspaces, enabling unbiased phenotypic analysis across biological scales.

MyoNet and AlveoliNet: A hybrid 3D neural-net pipeline for the instance segmentation and scoring of epithelial cells in intact mammary alveoli

The paper introduces two 3D neural networks for segmenting and scoring epithelial cells in cleared mammary tissue, demonstrating their use in quantifying myoepithelial cell proportions during pregnancy-lactation transitions.

Multiscale Symbolic Morpho-Barcoding Reveals Region-Specific and Scale-Dependent Neuronal Organization

This paper introduces MMB, a framework that encodes neuronal morphology into symbolic representations, revealing region-specific and scale-dependent principles of neuronal organization across the brain.

Presynaptic Actin Nanostructures: A Reproducibility Case Study

The paper attempts to reproduce findings from Bingham et al. on presynaptic actin structures using bioimage analysis, highlighting reproducibility challenges and the need for transparent methods.

Spatialproteomics - an interoperable toolbox for analyzing highly multiplexed fluorescence image data

The paper introduces spatialproteomics, a Python toolbox for analyzing highly multiplexed fluorescence images, demonstrating its use on lymph node and lymphoma data.

Large vision model framework for automated C. elegans analysis: From static morphometry to dynamic neural activity

TWARDIS automates C. elegans image analysis using AI models, improving accuracy and reducing manual effort in morphometry, behavior, and neural activity studies.

A Shape Analysis Algorithm Quantifies Spatial Morphology and Context of 2D to 3D Cell Culture for Novel Quantitation of Phenotypes

This paper introduces a shape analysis algorithm, LCPC, to quantify spatial morphology and context in 2D and 3D cell cultures, capturing features like chirality that traditional metrics miss.

NeuroFlow: An Integrated, Cross-Platform Workflow for Mouse Brain Atlas Registration and Quantification

NeuroFlow provides a browser-based workflow for registering and quantifying mouse brain histology without requiring additional software installation or remote server uploads.

Inferring Cell-Cell Interaction Dynamics from Cell Trajectory Data Using Deep Attention Networks

This paper introduces a deep attention network model to infer cell-cell interaction dynamics from trajectory data, providing interpretable insights into how interactions affect cell movement.

Multiscale learning and topological analysis across complex postures enable robust nematode size quantification in pharmacological assays

NemaSize is an AI pipeline that accurately measures nematode body size across complex postures, outperforming CellProfiler in curved and overlapping animals.

OpticalFlow3D: A tool for measuring amorphous motion in three-dimensional fluorescence microscopy images

OpticalFlow3D measures amorphous motion in 3D fluorescence microscopy images without requiring segmentation or prior motion definitions.

HiExM Enables Scalable Mapping of Organelle Morphology and Spatial Heterogeneity

HiExM enables scalable single-organelle analysis by improving spatial resolution and throughput, allowing detailed profiling of late endosomes and lysosomes.

Uncertainty-aware quantitative analysis of high-throughput live cell migration data

The paper introduces cellmig, a Bayesian tool for quantifying cell migration velocity with uncertainty, improving reproducibility and biological insight in high-throughput assays.

Dynamics of ML-based Morphological Features Indicate a Shear Stress-Dependent Bifurcation of hiPSC-Derived Endothelial Cell States

The paper uses ML to analyze morphological dynamics of hiPSC-derived endothelial cells under shear stress, identifying a bifurcation between two stable cell states.

A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy images

This paper introduces a noise-adaptive attention mechanism for microtubule segmentation in microscopy images, showing improved performance on synthetic and real datasets.

Deep learning-based decoding of axonal ultrastructure in gene-edited mice using electron microscopy imaging

The paper develops a machine learning framework to automatically quantify axonal and myelin features in electron microscopy images of gene-edited mice, showing correlations between myelin changes and mitochondrial density.

Cancer Phenotypic Plasticity Quantification using Morphology-Migration Coupled Metric in Live Label-Free Optical Microscopy

This paper introduces DSC, a metric to quantify cancer cell morphology-migration coupling in live label-free imaging, showing it captures non-genetic phenotypic plasticity.

Celldetective: an AI-enhanced image analysis tool for unraveling dynamic cell interactions

Celldetective is an AI-enhanced image analysis tool for analyzing dynamic cell interactions in immunology and immunotherapy assays.

Simultaneous quantification of dynamic bacterial deformation and motility by machine learning

This paper develops a machine learning method to quantify bacterial deformation and motility using convolutional neural networks, applicable to diverse transformable cells.

SpotMAX: a generalist framework for multi-dimensional automatic spot detection and quantification

SpotMAX is an AI-driven framework for automated spot detection and quantification in microscopy data, outperforming existing tools and human annotators across diverse biological applications.

Stars2Cells: Astrometric Tracking of Neurons Across Imaging Sessions

Stars2Cells tracks neurons across imaging sessions using a novel descriptor-based method, achieving high accuracy in identifying single neurons over time.

SImBA-SiQuAl: advancing high-content high-throughput phenotypic profiling of 3D microtumours

SImBA-SiQuAl is an open-source workflow for high-throughput quantitative analysis of 3D microtumours, enabling phenotypic profiling of spheroids and organoids.

Multi-Site Reproducibility Study of 3D High-Content Analysis with Dual-View Oblique Plane Microscopy

This study assesses the reproducibility of a 3D spheroid-based assay across four institutes using dual-view oblique plane microscopy and finds high consistency in treatment effects with low technical noise.

Semi-automated reconstruction of glomerular architecture from 3D confocal microscopy data

This study introduces a semi-automated method to segment and analyze glomerular architecture from 3D confocal microscopy data, reducing manual effort and improving standardization.

Connectome-scale self-supervised representation learning reveals neuronal organization beyond canonical labels

This paper develops a self-supervised framework for learning structure-connectivity representations in dense connectomes, revealing neuronal organization beyond canonical labels.

Connectome quality converges predictably to reveal optimal stopping points during proofreading

The paper introduces a method to estimate proofreading progress in connectomic datasets using global graph invariants, enabling optimal stopping points for reconstruction quality.

MCD Stitcher: An open-source tool for whole-slide stitching and conversion of Imaging Mass Cytometry data

MCD Stitcher converts proprietary .mcd IMC files into OME-TIFF images with automated stitching for whole-slide spatial analysis.