Cluster based harmonization (EUCAIM-SW-044_T-01-03-006)
https://bio.tools/cluster_based_harmonizationThe tool is designed to perform radiomics harmonization on large and heterogeneous datasets, where the risk of over-harmonization is present. Instead of directly applying harmonization based on predefined batch labels, the tool first identifies groups of batches that share similar characteristics through clustering of the radiomics data. It then performs harmonization using these cluster-derived labels. The tool allows the harmonization of radiomics variables using two methods: (1) original ComBat (Rabinovic, 2007) method, where each original batch group is considered for the harmonization process and (2) cluster-based ComBat method, where batch groups with similar radiomics characteristics form clusters and the latter are being considered for the harmonization process.
Sourced from
- bio.tools — cluster_based_harmonization
Related resources
This preprocessing tool is design for 2D digital mammograms in DICOM format. It standardizes and harmonizes images through a configurable pipeline that includes spatial reorientation, pseudo-3D stacking, isotropic resampling, intensity normalization, optional denoising, contrast enhancement, and mask processing (if available).
PureJsImage is a free, open-source TypeScript library for decoding, inspecting, processing, and converting ordinary images and scientific rasters in Node.js and modern browsers. It provides explicit readers for microscopy, whole-slide pathology, medical imaging, electron microscopy, spectroscopy, hyperspectral, and multidimensional array formats. These include OME-TIFF, OME-Zarr, Aperio SVS, DICOM, NIfTI, MRC/CCP4, NRRD, DigitalMicrograph, EMD, ENVI, and FITS. Range-backed readers can request selected regions, tiles, volume planes, and metadata while preserving native numeric samples where supported. The default package has no runtime dependencies. Optional JPEG and PNG WebAssembly accelerators require explicit registration.
This R package supports interactive visualization of multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques using shiny. The cytoviewer interface is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with SingleCellExperiment and SpatialExperiment objects for metadata visualization and supports image downloads.
A simple toolbox of two ImageJ plugins for quantifying adipocyte morphology and function in tissues and in vitro.
An interactive platform that performs statistical analyses on metabolomics datasets and allows visualising results with ease. The interface gives users autonomy in creating figures suited to their reporting and publication needs.
Desktop viewer for microscopy and whole slide pathology images on Windows and macOS. Opens whole slide scanner formats (Aperio SVS, Hamamatsu NDPI, MIRAX MRXS, Leica SCN, Ventana BIF) alongside acquisition formats (Zeiss CZI, Nikon ND2, DICOM, TIFF/OME-TIFF) in a single application, providing pyramid navigation of gigapixel images, metadata inspection, calibrated measurements, annotations, and on-device segmentation and object counting.