Oncosoft develops OncoStudio, an AI-driven software that automates the contouring of organs at risk and clinical target volumes in radiation therapy, achieving expert-level accuracy in under five minutes. This technology addresses the inefficiencies and time-consuming processes in treatment planning, enhancing productivity and precision in patient care.
Funding
$11.4M 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 treatment planning involves manual contouring of organs at risk (OAR) and clinical target volumes (CTV), which is a time-consuming and labor-intensive process. This manual contouring can lead to inconsistencies and inefficiencies, potentially impacting the accuracy and speed of treatment planning.
Solution
Oncosoft's OncoStudio is an AI-driven software designed to automate the contouring process for radiation therapy. OncoStudio uses AI algorithms to automatically detect and contour OARs and CTVs from CT, MR, and cone-beam CT images, achieving expert-level accuracy in under five minutes. The software streamlines the treatment planning workflow, reduces contouring time, and enhances the consistency of contouring results. By automating this critical step, OncoStudio enables clinicians to focus on patient care and personalized treatment strategies.
Target Audience
The primary target audience includes radiation oncologists, medical physicists, and other healthcare professionals involved in radiation therapy treatment planning.
Features
- AI-powered automatic contouring of over 100 OARs and CTVs
- Compatibility with CT, MR, and cone-beam CT imaging modalities
- Vendor-neutral operation, interfacing with all commercially available hardware and software according to the DICOM standard
- Institution-specific customization to optimize organ templates and contour styles
- Data-centric workflow aligned with data-centric processes in radiation oncology
- Compliant with global standards for medical imaging and broader healthcare information, supporting DICOM and HL7 FHIR
- Continuous model retraining with additional data and architecture updates
- Aims to expand to over 200 structures by 2025 and develop AI models for various imaging techniques such as MRI, Cone-beam CT (CBCT), and Megavoltage CT (MVCT)