A new AI-powered tool developed in Moscow checks chest X-ray quality in real time during procedures. The AI algorithm analyzes images in under 20 seconds and alerts radiology technicians to defects instantly, enabling on-the-spot corrections and avoiding patient return visits. Anastasia Rakova, Moscow's Deputy Mayor for Social Development, announced the development.

"Artificial intelligence in Moscow’s healthcare system is now addressing not only diagnostic challenges but also quality control. This new AI-powered algorithm, developed by Moscow scientists, automatically evaluates the quality of chest X‑rays—one of the most common imaging procedures. We can now assess image accuracy during the examination itself, in an average of just 17 seconds,” the deputy mayor noted.

Previously, radiology technicians had to perform these checks manually and often noticed errors only after the patient had left. Now, a neural network analyzes the image in real time, verifying correct patient positioning and accurate data entry. If any issue is detected, the system immediately alerts the specialist, who can retake the image on the spot without calling the patient back. A pilot project at three Moscow hospitals confirmed the method’s effectiveness: image quality assessment accuracy reached 94%, while data error detection achieved 99%."

The software integrates directly into radiographers' workstations for real-time operation. The new algorithm is capable of analyzing medical images across multiple parameters simultaneously, including the completeness of organ coverage, correct patient positioning, the absence of foreign objects in the image, and other key quality indicators.

The deployment of this quality control system is particularly valuable for screening programs and routine medical checkups, where chest X‑rays are a basic diagnostic method. Automating the process will allow radiologists to work with already verified images without wasting time interpreting low-quality ones.

"Technical errors in imaging acquisition sometimes necessitate repeat exams, burdening patients and the healthcare system," explained Yuri Vasiliev, Chief officer of Radiology at the Moscow Healthcare Department and Medical Director at the Center for Diagnostics and Telemedicine. “To optimize this process, we are implementing a software solution for radiology technician workstations that enables image quality assessment before the patient leaves the examination room. Specialists from the Center for Diagnostics and Telemedicine are already working on this project.”

 Moscow has been digitalizing its healthcare system for over a decade. Today, radiologists have access to more than 60 AI services across 43 modalities. The computer vision initiative is being implemented by specialists from the Center for Diagnostics and Telemedicine in collaboration with the Department of Information Technology. The project aligns with the objectives of the Moscow Healthcare Development Strategy through 2030.