Manteia Technologies

About Manteia Technologies

Manteia Technologies, established in 2017 in Xiamen, China, operates as a technology-driven company focused on providing vendor-independent software solutions for radiation therapy. The company's origins trace back to the Adaptive Research Group in the U.S., and its team comprises experienced physicians and medical physicists. The founder and CEO is Zhou Qichao.

The firm specializes in developing intelligent and adaptive solutions for cancer treatment, utilizing artificial intelligence, data analysis, and advanced algorithms. Manteia serves world-leading cancer centers, and its solutions have been implemented in over two hundred centers, impacting thousands of patients. The business model centers on the development and provision of specialized software for the radiation oncology market. Revenue is generated through the sale and licensing of its software products. The company has secured significant financial backing, raising a total of $30.7 million over four funding rounds. Its latest funding was a Series B round on January 18, 2024, for $15.4 million, led by Fujian Yangming Venture Capital. Other investors include Deyi Capital, REDHILL ​​CAPITAL, and Fosun.

Manteia's product portfolio offers a comprehensive suite of tools for radiation oncology. Key products include AccuContour™, a physician workstation with AI-contouring for RT image processing; AccuLearning™, a deep learning-powered local training platform; Mozi TPS, a next-generation treatment planning system; and a QA Solution for Monte Carlo patient quality assurance and machine quality control. These products aim to make oncology software faster and safer by enhancing precision, efficiency, and automation in treatment planning and delivery. The software is designed to be vendor-independent, allowing for seamless integration into existing clinical workflows. For instance, the MOZI Treatment Planning System (TPS) is a standalone software used to plan external beam irradiation with photon beams for patients with both malignant and benign diseases. It incorporates functions for image processing, structure delineation using deep learning for automatic contouring, treatment plan design, dose calculation with the Monte Carlo method, optimization, and evaluation.