Technology-invariant pipeline for spatial-omics analysis (Xenium / MERSCOPE / CosMx / PhenoCycler / MACSima / Hyperion) that scales to millions of cells

Integrated pipeline for multiplexed image analysis

astir | Automated cell identity from single-cell multiplexed imaging and proteomics 🖥🔬✨

Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications

Probabilistic topic model for identifying cellular micro-environments.

HistoJS: Web-Based Analytical Tool for Multiplexed Images. Limited Github Online Demo 👇

MIAAIM: Multi-omics Image Alignment and Analysis by Information Manifolds

An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data.

Rust library for reading imaging mass cytometry (IMC) data stored in .mcd files.

High-dimensional image preparation module for MIAAIM

SpatialVisVR is a VR platform tailored for advanced visualization and analysis of medical images in immuno-oncology. It allows real-time capture and comparison of mIF and mIHC images via mobile devices. Leveraging deep learning, it matches and displays similar images, supporting up to 100 protein channels.

High-dimensional image registration workflow as part of the MIAAIM framework. Hdi-reg is written in Python, and utilizes the Elastix library for computations.

Multi-omics image alignment and analysis by information manifolds (MIAAIM)

A workflow designed to perform multiplexed image analysis, specialising in (but not limited to) analysis of metal distribution in LA-ICP-TOFMS data.

Perform RESTORE normalization on multiplexed imaging data.

General importing and utility functions for high-dimensional image data