Multimodal data platform company Miso Information Technology said on Sunday it has secured technology to develop and commercialise the HQGAN (High-Quality Quantum GAN, HQGAN) model to address shortages of medical image data.

Development of the quantum computing-based medical data generation model, HQGAN, was carried out through joint industry-academia-research collaboration led by Miso Information Technology, including Bundang Seoul National University Hospital and Prof. Hyeong-won Yoo. It was promoted as part of Gangwon Techno Park's Gangwon Quantum Information and Communications Industry and Convergence R&D Support Programme.

Miso Information Technology said HQGAN generates high-quality medical images similar to real patient data. It said it secured improved performance compared with DCGAN (Deep Convolutional GAN) and WGAN-GP (Wasserstein GAN-Gradient Penalty) in terms of structural consistency, detailed lesion expression and image quality.

It said this is expected to ease the burden on medical institutions adopting AI, including improving AI training accuracy, reducing the cost of securing medical data and shortening the time needed to build datasets.

A Miso Information Technology official said, "AI performance is ultimately determined by data quality." The official added, "By combining quantum technology with multimodal data platforms and agentic AI service capabilities, we will support the advancement of medical AI diagnosis and secure technological competitiveness in the global digital healthcare market."