Work

A comprehensive software solution for Steiner's cephalometric analysis: Integrating machine learning for enhanced accuracy

Year: 2025

Type: article

Abstract: Cephalometric analysis is one of the most essential tools in orthodontic diagnosis and treatment planning, with Steiner's analysis being a gold standard for evaluating skeletal and dental relationships. However, manual landmark identification is time-consuming and prone to variability. This study introduces a Python-based software tool that automates Steiner's analysis using Tkinter for GUI, Pillow for image processing, and machine learning (ML) for landmark refinement. The software improves efficiency while maintaining clinical reliability, demonstrating potential for AI-assisted orthodontic diagnostics. Machine learning component makes it fail safe, software can be corrected with mistakes retrained.

Source: Bioinformation

DOI: 10.6026/973206300213885

Authors: Vinay V Bedre, Sushil Mahajan, Trilok Shrivastav

Institution: People’s University

Language: English

Topic: Orthodontics and Dentofacial Orthopedics

Subfield: Orthodontics

Field: Dentistry

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4415948063