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Bio-informed Image-based Deep Learning Frameworks for Prognosis of Pediatric Spinal Deformities

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
Active Model-Based Inference for Muscle Strength Diagnostics

Description:

Muscle strength assessment is a standard part of any clinical evaluation. Due to the kinematic and muscular redundancy in the human musculoskeletal system, muscle strength can not be measured directly in vivo. Clinicians utilize specific postures and forces to bias the muscles of interest, then infer the muscle strength from...

Keyword:

Active Learning , Parameter Estimation , Musculoskeletal Model, and Cervical Spine

Subject:

Mechanical engineering and Biomechanics

Creator:

Abbott, Rebecca Elizabeth

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

04/15/2021

Date Created:

2021-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_797807 and http://dissertations.umi.com/northwestern:15487

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Bio-informed Image-based Deep Learning Frameworks for Prognosis of Pediatric Spinal Deformities

Active Model-Based Inference for Muscle Strength Diagnostics

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