Data-driven formulation of surgical procedures through virtual planning

Abstract

This presentation introduces a data-driven strategy to mathematically extract dominant features of surgical procedures and synthesize patient-specific surgical plans from past planning data. The overall framework is developed based on the sparse coding theory. The preliminary experiments demonstrate the efficacy of sparse coding from virtual planning database and show the findings on data-driven formulation of mandibular reconstruction procedures.