The Center for Diagnostics and Telemedicine and Beijing University of Technology have announced the launch of a strategic partnership aimed at advancing algorithms to enhance the quality of ultrasound imaging and improve diagnostic accuracy. The collaboration, which brings together leading Russian and Chinese scientists, is particularly focused on increasing the early detection rates of breast cancer.

Yuri Vasilev, Chief Consultant for Diagnostic Imaging of the Moscow Health Care Department, emphasized the importance of international collaboration in the medical field.

“Expanding international cooperation in medical education and research is one of our top priorities,” Vasiliev said. “This partnership with Beijing University of Technology—a leading technical institution in China—marks a significant step forward in advancing medical technologies and enhancing breast cancer diagnostics. The agreement paves the way for sharing expertise and implementing innovative solutions in Russian healthcare institutions.”

Under the agreement, the two institutions will exchange scientific materials and research experience, jointly develop new mathematical models and data analysis methods, co-author scientific articles, and participate in international conferences.

Anton Vladzimirsky, Ph.D. in Medicine, D.Sc. and Deputy Director for Research at the Center for Diagnostics and Telemedicine, highlighted the mutual benefits of the partnership. “Our Chinese colleagues are interested in our expertise in producing and applying medical phantoms for equipment calibration and specialist training in diagnostic ultrasound. Conversely, we are keen to learn from their approach to designing mathematical algorithms for signal processing. By combining our international expertise, we can develop more advanced ultrasound imaging algorithms, ultimately improving diagnostic accuracy for socially significant diseases,” Vladzimirsky said.

To date, Moscow researchers have developed 12 medical phantoms that mimic human tissues, organs, and anatomical structures. These phantoms fall into two primary categories: those used for training healthcare professionals and those used for calibrating diagnostic equipment. The use of phantoms enables practitioners to refine their techniques for critical diagnostic procedures and ensures devices are properly prepared for clinical use.

Zhuhuang Zhou, Ph.D., Associate Professor., Dept. of Biomedical Engineering College of Chemistry and Life Science at Beijing University of Technology, noted the value of this collaboration: “We are pleased to work with the Center for Diagnostics and Telemedicine.  We share a common scientific goal—to develop algorithms that enhance ultrasound diagnostics. The experience of our Moscow colleagues, particularly in creating medical phantoms, is of great interest to us. We plan to use these phantoms to test and refine new artificial intelligence algorithms before proceeding to clinical trials. The accuracy and realism of these models are vital to the validity of our research. We are confident that this scientific partnership will enable significant progress in healthcare innovation.”

The Center for Diagnostics and Telemedicine, operating under the Moscow Healthcare Department, is a leading scientific and practical institution driving innovation in medical diagnosis and digital healthcare. The Center specializes the management of radiology departments, and the integration of artificial intelligence (AI) technologies into clinical practice. The Center is also dedicated to scientific research and the training of medical professionals.  Since 2013, the Center’s team has produced over 800 scientific publications, including articles, methodological guidelines, monographs, and training manuals, and has registered more than 200 intellectual property results.

A pioneer in digital transformation, the Center has played a central role in Moscow’s large-scale experiment with computer vision and AI in medicine. Since 2020, the Center has been conducting an experiment focused on integrating computer vision technologies into medical practice. As part of this initiative, neural networks have analyzed over 14 million medical images with a high degree of accuracy, demonstrating the transformative potential of artificial intelligence in enhancing diagnostic precision and efficiency within healthcare settings.

Beijing University of Technology (BJUT) is recognized as one of China’s foremost technical universities and a major center for education and research. BJUT has made significant contributions to the advancement of science and technology in China and is actively engaged in international collaboration, implementing joint educational programs and research projects with leading universities and scientific