4 results match your criteria: "11-263 Donadeo Innovation Centre for Engineering[Affiliation]"
Answer to the Letter to the Editor of S. Pan, et al. concerning "The test-retest reliability of frontal, sagittal, and transverse spinal measurements during three standing arm positions in adolescents with idiopathic scoliosis measured using ultrasound imaging" by B.J. Fehr, et al. (Eur Spine J [2024]: doi: 10.1007/s00586-024-08576-0).
Eur Spine J
January 2025
Department of Physical Therapy, Faculty of Rehabilitation Medicine, University of Albert, 2-50 Corbett Hal, Edmonton, AB, T6G 2G4, Canada.
A fully automated measurement of migration percentage on ultrasound images in children with cerebral palsy.
Med Biol Eng Comput
December 2024
Department of Electrical and Computer Engineering, University of Alberta, 11-263 Donadeo Innovation Centre for Engineering, 9211-116 St, Edmonton, AB, T6G 1H9, Canada.
Migration percentage (MP) is the gold standard to assess the severity of hip displacement in children with cerebral palsy, which is measured on anteroposterior hip radiographs. Recently, the ultrasound (US) method has been developed as a safe alternative imaging modality to image and monitor children's hips. However, measuring MP on US images (MP) is time-consuming, challenging, and user-dependent.
View Article and Find Full Text PDFValidity of machine learning algorithms for automatically extract growing rod length on radiographs in children with early-onset scoliosis.
Med Biol Eng Comput
January 2025
Department of Electrical and Computer Engineering, University of Alberta, 11-263 Donadeo Innovation Centre for Engineering, 9211-116 St, Edmonton, AB, T6G 1H9, Canada.
The magnetically controlled growing rod technique is an effective surgical treatment for children who have early-onset scoliosis. The length of the instrumented growing rods is adjusted regularly to compensate for the normal growth of these patients. Manual measurement of rod length on posteroanterior spine radiographs is subjective and time-consuming.
View Article and Find Full Text PDFAssessment of hip displacement in children with cerebral palsy using machine learning approach.
Med Biol Eng Comput
September 2021
Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada.
Manual measurements of migration percentage (MP) on pelvis radiographs for assessing hip displacement are subjective and time consuming. A deep learning approach using convolution neural networks (CNNs) to automatically measure the MP was proposed. The pre-trained Inception ResNet v2 was fine tuned to detect locations of the eight reference landmarks used for MP measurements.
View Article and Find Full Text PDF