Stem Cell Analysis Navigator
© 2025 S. Tritley, C. Rouse, E. Brey, A. Qutub
Platform: Python, Java, etc
Summary: Open-source software workbench with BigDataViewer/BigStitcher for Lightsheet, Sci-Java plugin ecosystem, etc.
Platform: Python, Plugins
Summary: Modular pipelines (v. 4) with object analysis and classification (Cell Painting, etc) features.
Platform: ImageJ
Summary: Semi-automated processing of large sets of neuronal images.
Platform: ImageJ
Summary: Automated tracing of neurites from fluorescence images.
Platform: Web
Summary: Collaborative annotation of large EM volumes. Remote tracing, connectomics queries.
Platform: Python
Summary: Interactive learning and segmentation toolkits for complex datasets.
Platform: Fiji macro/plugin
Summary: High-throughput rapid neurite outgrowth quantification from 2D images.
Platform: ImageJ
Summary: ImageJ plugin for neurite outgrowth quantification.
Platform: ImageJ
Summary: ImageJ plugin for neurite outgrowth quantification. 10.1007/ s12021-011-9134-2
Platform: Unknown
Summary: Single cell models to map single cell models to map single neuron traces and stitch volume electron microscopy
Platform: C++, Python
Summary: Software for tracking cells and analyzing 3-dimensional microscopy images
Platform: ImageJ
Summary: Open-source ImageJ plugin for analysis of spine morphology
Platform: MATLAB
Summary: Neurite outgrowths in spinal cord neuronal root ganglia
Platform: ImageJ
Summary: Batch processing of landscape images for neuronal morphology.
Platform: MATLAB
Summary: Traces neurites and cell bodies, quantifies neurite-neurite populations
Platform: ImageJ
Summary: Quantifies morphology of neurons and density of neurite networks.
Platform: MATLAB
Summary: 3D neuron reconstruction, dendritic spine analysis.
Platform: Windows
Summary: Extracts neuronal data from low-quality images using LoG and graphical models.
Platform: C++/Qt
Summary: Open-source SIM-based software for tracing with parallel (CPU) trees and plugins.
Platform: Windows
Summary: Individualized tracing/tracking of neurons.
Platform: MATLAB
Summary: Decomposes neuronal arbors into dendrites from morphological Micro-CT volumes.
Platform: Web - Python
Summary: Deep learning library for single-cell analysis from images.
Platform: Java, Scripting, Plugins
Summary: WSi module with batch processing, integrates StarDist, WSi deconvolution.
Platform: ImageJ
Summary: Resolves cell-by-cell morphology, individual neurites, etc.
Platform: C++, Cross-platform
Summary: 3D reconstruction, tracing, cell-pop visualization, connectomics analysis.
Platform: Python
Summary: Morphometric analysis and visualization of 3D-reconstructed neurons.
Platform: Python (Blender addon)
Summary: Software for m-Rotundus H51 image analysis.
Platform: ImageJ
Summary: 3D semi-automated tracing and reconstruction, includes Sholl analysis, etc.
Platform: Python
Summary: Deep learning tools for neuron tracing.
Platform: Unknown
Summary: Extracts synaptic vesicles from EM images.
Platform: Python
Summary: Method for analyzing single-cell gene expression data.
Platform: Python
Summary: Task for analyzing single-cell gene expression data.
Platform: MATLAB
Summary: UL model for star-convex objects/nuclei segmentation with D-H capacity, Python.
Platform: Command line
Summary: Analysis pipeline for single-cell DNA sequencing data.
Platform: Fiji, Python
Summary: Set of tools (ST viewer, UMAP) for analysis of spatial transcriptomics data.
Platform: Web-based
Summary: Visualization tool for GeoMx digital spatial profiler data readouts.
Platform: Promoters
Summary: Python tool for GeoMx digital spatial profiler data.
Platform: Python, TensorFlow
Summary: Fast and accurate deconvolution of spatial transcriptomics data.
Platform: Python, R
Summary: Efficient and scalable analysis of spatial molecular data.
Platform: C++, Go, Rust, Python, R
Summary: Analysis pipeline for Visium Spatial Gene Expression data.
Platform: Python, Pytorch
Summary: Domain-optimized and training/inference tasks for biomedical imaging.
Platform: Python, Deep learning based
Summary: Toolbox for brightfield/fluorescence images with custom workflows.
Platform: Python
Summary: Measures and classifies neurites, detects variations in neurite growth.
Platform: Pytorch
Summary: Performs cell-in-cell models, 2D/3D segmentation, slicing, export and contributor diagnostics.
Platform: Python GUI, Jupyter
Summary: Semi-automated 2D/3D tracing, export SWC/SVG files, morphometrics and Sholl analysis.
Platform: MATLAB, R
Summary: Pipeline for 3D cell segmentation and analysis.
Platform: R
Summary: Reversible method for spatial gene expression analysis.
Platform: Python
Summary: Weighted graph from wavelet-tree segmentation. Cell classification via SVM and Grad-CAM.
Platform: Deep learning platform
Summary: Segments brightfield images, tracks neurites, evaluates morphology.
Platform: Fiji plugin + web-based
Summary: End-to-end and unified analysis tool, neighborhood graphs, interconnects with Giotto Invest.
Platform: R
Summary: End-to-end and unified analysis tool, neighborhood graphs, interconnects with Giotto Invest.
Platform: Web app (Python)
Summary: Method for discovering spatial transcriptomics data
Platform: Python + R
Summary: Collab-enabled tool to triangulate 2L models (scanpy, Giotto, Seurat) for integration with single-cell data.
Platform: Windows
Summary: UL modeling, image classification and segmentation, integration with Caffe.
Platform: Web + Python
Summary: Builds spatial/partitioned graphs from matrices or radiance for large-scale network profiling.
Platform: Python + R
Summary: Unifies data and molecular profiles, neighborhood graphs, preparation for downstream analyses.
Platform: Command line
Summary: Analysis pipeline for Xenium in-situ data.
Platform: Windows
Summary: Filament Tracer for organoids/neurons, batch analysis, vesicle/organelle/object tracking, object-object / object-group/ i-graphlet analysis.
Platform: R
Summary: Seurat v.5 integrates RNA-seq with spatial transcriptomics data.
Platform: Web-based, React, Python,
Summary: Visualization tool for multi-omics single-cell data.
Platform: Python
Summary: Integrated platform for single-cell and spatial omics analysis.
Platform: Python
Summary: High-throughput image-processing software for quantifying DNA damage and nuclear size.
Platform: Python
Summary: Automatic detection of neural boundaries, calculating neurite length and number.
Platform: Open-source (Python-based)
Summary: Semi-automatic pipeline for processing up to 10-Terabyte images for 3D reconstruction and tracing, Sholl and connectome analysis, cell and sub-cellular distribution.
Platform: Cloud-based
Summary: AI platform for multiplex immunofluorescence data analysis, including cell segmentation, phenotyping, and high-throughput processing.
Platform: ImageJ-based
Summary: Automated pipeline for detecting synapses from immunofluorescence images, using Stardist and SynQuant for thresholding and puncta.
Platform: Binary (pipeline)
Summary: Analysis pipeline for Visium Spatial Gene Expression data. Integrates imaging data from CytAssist, provides automatic image processing and control and performs segmentation.
Platform: Python, Blender, Unity
Summary: Automated image processing for volumes, including cortical thickness, tissue segmentation, and neuronal tracing/rendering.
Platform: Web, Python, MATLAB
Summary: Builds spatial/functional graphs from masks or calcium time series; network metrics.
Platform: Web, Python, MATLAB
Summary: Cloud-based platform for 2D/3D image analysis with community/own modules, trainable DL models.