Forecasting the Anterior Cruciate Ligament Rupture Patterns - Robotics Institute Carnegie Mellon University

Forecasting the Anterior Cruciate Ligament Rupture Patterns

Portrait of Forecasting the Anterior Cruciate Ligament Rupture Patterns
This Project is no longer active.

Complex knee injuries are common, often resulting from multiple forces (e.g. rotational, varus-valgus loading, anterior/posterior displacement). Identification of the specific injury pattern of the Anterior Cruciate Ligament (ACL) and other knee structures using non-invasive methods may improve pre-operative planning and guide treatment, reduce costs and facilitate high-quality patient care. The main goal of this project is to present a classification system based on a set of non-invasive measures and state-of-the-art machine learning techniques to preempt the exact ACL rupture pattern.

current staff

past staff

  • Freddie H. Fu
  • Jim Starman