Voxel Healthcare builds AI-driven tools that automate brain structure segmentation and optimize radiation therapy planning, aiming to reduce side effects for pediatric cancer patients. Their flagship product, ClickBrainRT, serves as a clinical ally for radiation oncologists and physicists by providing precise treatment path recommendations and facilitating advanced knowledge sharing. The platform leverages deep learning to deliver accurate, repeatable segmentations that improve treatment outcomes and workflow efficiency.
Funding
$225K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Radiation therapy for brain tumors often relies on manual segmentation of brain structures, which is time‑consuming and prone to variability. Inaccurate segmentation can lead to excess radiation exposure to healthy tissue, increasing side effects, especially in pediatric patients.
Solution
Voxel Healthcare’s ClickBrainRT platform applies AI‑driven segmentation to automatically delineate brain anatomy from imaging data, providing consistent and precise contours for treatment planning. The software integrates these segmentations into radiation therapy workflows, enabling oncologists and medical physicists to optimize dose distribution and spare healthy tissue. By reducing manual effort, ClickBrainRT shortens planning time and supports more accurate, patient‑specific treatment plans. The platform also includes a knowledge‑sharing module that captures planning insights and outcomes, facilitating continuous improvement across treatment teams and institutions.
Target Audience
Primary users are radiation oncologists and medical physicists at pediatric oncology centers and hospitals that deliver brain radiation therapy.
Features
- Deep learning models trained on pediatric neuroimaging for automated, high‑resolution brain structure segmentation
- Seamless export of AI‑generated contours to major treatment planning systems (e.g., Eclipse, RayStation)
- Dose‑optimization engine that suggests radiation plans minimizing exposure to critical structures
- Integrated knowledge base that aggregates case data, plan metrics, and outcome feedback for team collaboration
- Validation tools that compare AI segmentations with expert annotations to ensure clinical safety
- User interface designed for radiation oncologists and physicists with minimal training required