A streamlined software platform that transforms raw imaging data from 3D cancer model assays into clear, quantitative insights with minimal user input

Proposed Uses

3DcX is designed to support researchers working with organoid, spheroid, and cell鈥憈herapy assays by automating the analysis of time鈥憀apse imaging data.

It enables rapid interpretation of treatment effects, supports screening workflows, and reduces the time and manual effort typically required for 3D assay analysis.

Problem addressed

Analysis of 3D cancer models is often slow, subjective, and fragmented across multiple tools.

Existing software often fails when faced with low鈥慶ontrast imaging, late鈥憇tage degradation, or substantial object movement in time鈥憀apse datasets, and many systems are restricted to proprietary microscope ecosystems.

3DcX overcomes these challenges by replacing manual, bias-prone steps, ensuring stable tracking under poor imaging conditions, and generating reproducible, time鈥憆esolved metrics across diverse imaging systems.

Technology Overview

3DcX provides an integrated environment for processing and analysing time鈥憀apse datasets from 3D cancer assays. The platform ingests standard image and video formats, identifies relevant structures, assesses their viability, and tracks their behaviour throughout the experiment to generate clear, quantitative and visual outputs.

Designed to cope with movement, low contrast, and structural collapse, it smooths and stabilises lower鈥憅uality inputs to ensure reliable performance. Its microscope鈥慳gnostic design supports a wide range of imaging setups, and the fully automated workflow delivers consistent, experiment鈥憆eady results with minimal user intervention.

 

Benefits

  • Automated, unbiased analysis of 3D assay data
  • Compatible with images from any microscope
  • Performs reliably across different imaging conditions
  • Supports time-based assessment of growth viability, and treatment effects.
  • Delivers clear, quantitative metrics and visual outputs
  • Suitable for both exploratory and higher throughput workflows

Contact for this technology

Commercialisation Officer, Faculty of Natural Sciences

Emily Russell