Algin Oktay and colleagues have published “Pediatric bone age assessment with AI models based on modified Tanner-Whitehouse” in Al-Qadisiyah Journal for Engineering Sciences (March 2026).
Estimating bone age from hand X-rays helps doctors assess children’s growth and is also used in legal cases, but manual reading is slow and varies between readers. The study proposes an AI system that first finds the relevant regions of the hand and then analyzes them with several networks, trained on 12,600 X-rays from an RSNA challenge dataset. Automated assessment could make bone age estimates faster and more consistent.
Authors: Mohammed Radeaf, Hadeel K. Aljobouri, Noor K.N. Al-Waely, Algin Oktay