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Description:: Predicting pediatric spinal deformity (PSD) from X-ray images collected on the patient's initial visit is a challenging task. This research provides a bio-informed framework based on a mechanistic machine learning technique with dynamic patient-specific (PS) parameters to predict PSD. We provide a geometry-based bone growth model that can be utilized...
Keyword:: Adolescent idiopathic scoliosis (AIS), Mechanistic bio-informed machine learning, Pediatric spinal deformity (PSD), 3D reconstruction, X-ray images, and Mesh registration
Subject:: Mechanical engineering and Biomechanics
Creator:: Tajdari, Mahsa
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 06/22/2022
Date Created:: 2022-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_879756 and http://dissertations.umi.com/northwestern:15944

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