Research developed by experts at Children’s Hospital of Philadelphia (CHOP), was recently published online by Public Library of Science (PLOS) One. The findings have the potential to advance the care of children living with spinal differences.
Led by Saba Pasha, PhD, the Director of Orthopaedic Engineering in the Division of Orthopaedics at CHOP, the study aims to change the methods currently used to detect spinal differences by using X-rays only. Thus far, a time-consuming image processing was required to obtain this information. However, this breakthrough finding allows clinicians to obtain information regarding the true curvature of the spine from the clinically available medical images.
This collaborative study between the Division of Orthopaedics and the Department of Radiology at CHOP opens a new avenue for exploring treatment options. According to Pasha, “the aim of this study was to develop a method that can provide adequate information regarding the patients’ spinal deformity that fits in the busy clinical practice. The application of machine learning and artificial intelligence shows exciting future for patient care in the field of pediatric spinal deformity.”
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Research developed by experts at Children’s Hospital of Philadelphia (CHOP), was recently published online by Public Library of Science (PLOS) One. The findings have the potential to advance the care of children living with spinal differences.
Led by Saba Pasha, PhD, the Director of Orthopaedic Engineering in the Division of Orthopaedics at CHOP, the study aims to change the methods currently used to detect spinal differences by using X-rays only. Thus far, a time-consuming image processing was required to obtain this information. However, this breakthrough finding allows clinicians to obtain information regarding the true curvature of the spine from the clinically available medical images.
This collaborative study between the Division of Orthopaedics and the Department of Radiology at CHOP opens a new avenue for exploring treatment options. According to Pasha, “the aim of this study was to develop a method that can provide adequate information regarding the patients’ spinal deformity that fits in the busy clinical practice. The application of machine learning and artificial intelligence shows exciting future for patient care in the field of pediatric spinal deformity.”
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