Towards Automatic Generation of Patient-Specific Knee Models

The objective of the current paper is to present a pipeline designed to reduce the pre-processing time required to build subject-specific finite element knee models and facilitate their clinical integration. The pipeline involves development and validation of an atlas model of the knee joint and features of the TwInsight software suit that use novel methodologies such as: 1) deep learning for automatic segmentation of the bones from computed tomography scans, 2) automatic generation of finite element meshes with hexahedral elements, and 3) anatomical inference algorithm to adapt the atlas model to the morphology of a subject and result in the subject’s personalized biomechanical model.