Image Analysis
Showing 36 of 38 projects
Analyze and compare images in JavaScript and Node.js with features like color analysis, visual diffing, and antialiasing detection.
A zero-footprint, configurable, and extensible web-based medical imaging viewer for DICOM and oncology data.
A fast, interactive, multi-dimensional image viewer for Python designed for browsing, annotating, and analyzing large scientific images.
A free, open-source multi-platform software for 3D visualization and medical image analysis.
A C library for efficient image processing and analysis, widely used in OCR and computer vision applications.
A command-line tool that detects steganographically hidden data in PNG and BMP image files.
A Flutter plugin for embedding a fully customizable, feature-rich camera experience in Android and iOS apps.
A Ruby wrapper for OpenCV, enabling computer vision and image processing in Ruby applications.
An open-source image analysis software package for plant phenotyping using computer vision.
A Ruby wrapper around the pHash library for detecting duplicate and near-duplicate images using perceptual hashing.
A free Google Colab-based toolbox with Jupyter notebooks and GUI for applying deep learning to microscopy data without coding expertise.
A Python interface for interactive web-based visualization of multidimensional images, point sets, and geometry in Jupyter notebooks.
A pure JavaScript medical research image viewer for DICOM and NIFTI formats with advanced visualization tools.
A scalable Python toolkit for analyzing and visualizing spatial molecular data from tissue sections.
A comprehensive image processing library for Julia, providing tools for loading, manipulating, and analyzing images.
An open-source toolkit for scalable, standardized computational pathology analysis, enabling AI and machine learning on large imaging datasets.
A generic C++ library for image analysis and computer vision using template-based generic programming.
A Go library for detecting nudity in images, ported from nude.js.
A deprecated Node.js sample application demonstrating IBM Watson Visual Recognition service features.
A TensorFlow-based object detection model that localizes and identifies multiple objects in images using SSD MobileNet V1 or Faster R-CNN ResNet101.
An open and extensible Fiji plugin for single-particle tracking in life-science microscopy images.
A PyTorch-based Python package for deep and machine learning analysis of microscopy data, designed for domain scientists.
Automated 3D cell detection and classification in large-scale volumetric brain images using deep learning.
Open-source software and data format standards for storing and manipulating biological light microscopy data.
A curated list of software, tools, pipelines, and plugins for image analysis in biological research.
Interactive exploration and analysis software for large, high-dimensional image-derived biological data with supervised machine learning.
A collection of tools and scripts to automate microscopy workflows in ZEN Blue using Python, APIs, and AI tools.
A web-based DICOM slide microscopy viewer and annotation tool for imaging data science and computational pathology.
A Python package for processing and normalizing high-dimensional morphological feature data from high-throughput cell imaging experiments.
A Python library for interacting with QuPath, providing a pythonic interface to manage and analyze digital pathology projects.
A library of mathematical morphology methods and plugins for ImageJ, extending its capabilities for 2D/3D image analysis.
An automated pipeline for organelle segmentation, tracking, and hierarchical feature extraction in 2D/3D live-cell microscopy.
A Julia package providing multiple algorithms for non-negative matrix factorization, including multiplicative updates, ALS, coordinate descent, and separable NMF.
A curated list of software, datasets, and publications for image-based profiling of biological phenotypes in drug discovery and cell biology.
A curated list of software, datasets, and publications for image-based profiling of biological phenotypes in drug discovery and cell biology.
An R package for image processing and analysis with a focus on microscopy and biological imaging.
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