Indica Labs: Learn how to unlock deeper insights and enhance your data using the HALO Spatial Analysis module
Masterclass: Performing Spatial Analysis Workflows with HALO®
Date: 19 May 2026
Time: 8:00 – 9:00 PDT | 11:00 – 12:00 EDT | 16:00 – 17:00 BST
Location: Webinar
Summary
The HALO® Spatial Analysis module enables quantitative assessment of cellular spatial relationships within whole-slide images, providing a clear and reproducible way to study spatial biology in brightfield and fluorescence tissue images and supporting richer, more informative data outputs. Join Indica Labs for a masterclass exploring the key steps in a spatial analysis workflow: validating object data, defining biologically relevant cell populations via filtering, and generating interactive spatial plots. David Cordover, Field Applications Scientist, will discuss the algorithms included in the module—nearest neighbor, proximity, infiltration, and density heatmaps—and demonstrate how they enable users to measure cell–cell distances, assess spatial proximity within defined radii, quantify cellular infiltration across tissue interfaces, and visualize regional cell density patterns.
David will also explore the Spatial Analysis module’s data visualization capabilities, including customizable plot layers, histograms, color‑scaled heatmaps, and markup images, and walk through how they support both quality control and biological interpretation. Advanced features for saving and reusing spatial analysis settings, batch processing across studies, and exporting detailed summary metrics, object‑level data, plots, and reports for downstream statistical analysis will also be highlighted.
Learning Objectives
- Learn how to prepare and use cell and object data for spatial analysis in HALO
- Run and understand key spatial analysis tools, including nearest neighbor, proximity, infiltration, and density heatmaps
- View and adjust spatial results using plots and markup images
- Run analyses on multiple images, save settings, and export results for further use
Presenter
David Cordover
Field Applications Scientist
Indica Labs
David Cordover is a research field scientist with over 20 years of experience supporting research in large biopharma, biotech, and CRO organizations. His career spans roles at AMGEN, Takeda, Akoya Biosciences, and small CRO’s specializing in histology and digital pathology. For most of his career he has focused on AI‑ and ML‑driven image analysis, digital pathology, and quantitative biomarker discovery. David has led high‑impact biomarker programs from preclinical research through IND stages, working with multiple image analysis platforms and whole‑slide scanners, including HALO AI and Akoya technologies.
SOURCE: Indica Labs
