Scientific image analysis resources and software tools.
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Updated
Jul 15, 2026
Scientific image analysis resources and software tools.
Scientific Dataset Quality Control and Data Exploration Tool
🔭🪐☄️ Reproducible, scriptable stacking pipeline for DWARF 3 smart telescope FITS data with transparent frame selection, registration, and science-grade linear outputs.
Repository to Control Camera
A Qt-based desktop photo editor featuring a two-pane workflow and a powerful, asynchronous plugin architecture built on nexuslua.
High-performance, browser-based spectral imaging suite. Real-time PCA-driven enhancement for rock art, archaeology, and forensics. Includes a live mobile scanner and a professional desktop editor.
A C# native ImageJ-like scientific image analysis application for Windows.
Validated Micro-Manager BeanShell scripting examples: XYZ stage control, 2D scanning, spectral mapping, and multi-camera acquisition, including with different ROI. MM 1.4 & 2.0.
GPU-accelerated 3D volumetric stitcher for tomographic and microscopy datasets
💎 LTS Industrial Standard: PDF/Word optimization with scientific Trellis Mimic engine. Features Turbo Parallel processing & Global Camouflage (Ricoh/Fujitsu/Canon 2025 profiles). Embedded Python 3.12, zero-install, no admin needed. Ultimate document privacy for Windows LTSC/Enterprise.
A C++ library for image I/O using ImageMagick and cfitsio, designed as a nexuslua plugin for asynchronous image processing.
Collection of LabView subVIs for acquisition from Photometrics Prime 95B camera using PVCAM SDK
A PyQt6 GUI for scientific image analysis, simplifying batch processing, contrast enhancement, and heatmap generation. Features AI-powered segmentation and quantification using the Segment Anything Model (SAM).
CSV-driven batch processing for microscopy images: 16-bit TIFF normalisation, cropping, and calibrated scale bars
A header-only C++ library for type-safe, high-dynamic-range image containers and fundamental image processing utilities.
Automated 360° image acquisition pipeline for ML-ready dataset collection in quantum sensing research. Synchronizes a Thorlabs scientific camera with a KIM101 motor controller to capture biological specimens (insect/arachnid parts) at 0.5°/1° angular resolution.
A resource-efficient, CPU-only pseudo-label generation framework for CT scans and scientific imaging, outperforming GPU-based SAM on segmentation tasks.
napari plugin for editable single-cell confocal ROI analysis with cell and vacuole segmentation
Turn your Android phone into a calibrated scientific imaging instrument. 16.8µm resolution, 688mm composite stitching, live tap-to-measure. Built in one day on-device
Image preprocessing pipeline for bug-skin microscopy images — sharpness detection, frame selection, synthetic blur generation, and patch extraction to create ML training pairs for supervised image restoration.
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