Moscow launches 70th healthcare AI tool to automate pediatric hip dysplasia diagnostics

RUSSIA—Moscow’s healthcare system has launched its 70th artificial intelligence (AI) service for radiology, introducing a digital tool that analyzes hip X-rays in children and automates complex measurements used to detect developmental hip dysplasia.

The initiative, announced by Anastasia Rakova, Deputy Mayor of Moscow for Social Development, expands the use of AI in medical imaging while supporting radiologists in pediatric diagnosis.

AI automates complex hip measurements

The new service automates coxometry, a process that involves identifying specific anatomical landmarks and calculating angles to assess the position and alignment of structures within the hip joint.

These measurements are particularly important when physicians suspect developmental dysplasia, a condition in which the hip joint does not develop normally.

The AI tool plots the required angles directly on X-ray images, reducing the time and technical effort needed to perform the measurements.

Physicians can then use the AI-generated results alongside the child’s clinical information and other imaging findings when preparing their reports and making diagnostic assessments.

“Today, Moscow radiologists have 70 AI services at their disposal, each designed to improve the speed and precision of medical image analysis. This newest tool is a significant advancement for pediatrics,” said Rakova.

She added that accurately measuring joint angles and assessing bone alignment are critical when evaluating a child’s hip.

By automating these measurements, the technology allows physicians to prepare reports more efficiently while supporting the expansion of digital diagnostic services.

AI applications expand across radiology

Meanwhile, Moscow has continued to broaden the use of AI across its radiology services.

In addition to the new coxometry algorithm, specialists now have access to tools that support complex abdominal computed tomography (CT) analysis, automatically identify radiographic signs of knee osteoarthritis, and perform morphometric analysis of brain magnetic resonance imaging (MRI) scans.

Clinicians can also compare the outputs of multiple AI algorithms when reviewing medical images.

This capability can help them identify subtle or difficult-to-detect changes that may require further assessment.

Moscow currently uses AI technologies across 45 clinical areas in radiology. The systems support tasks including image analysis, patient triage and faster report generation.

However, the digital services remain supportive tools rather than replacements for medical professionals.

Radiologists and other clinicians retain responsibility for final clinical decisions, combining AI-generated findings with patients’ medical histories, symptoms and comorbidities.

Six years of AI development

Moscow’s healthcare system has piloted computer vision technologies in radiology for six years.

The programme is coordinated by the Center for Diagnostics and Telemedicine of the Moscow Health Department in collaboration with the Moscow Department of Information Technology.

The Center for Diagnostics and Telemedicine is a scientific and practical institution within Moscow’s healthcare system.

It focuses on advancing imaging and instrumental diagnostics, supporting digital transformation, introducing AI into clinical practice, conducting research and providing professional education.