Using hierarchical unsupervised learning to integrate and reduce multi-level and multi-paraspinal muscle MRI data in relation to low back pain.
Abel Torres-EspinAnastasia KellerGabriel T A JohnsonAaron J FieldsRoland KrugAdam R FergusonAlan R HargensConor W O'NeillJeffrey C LotzJeannie F BaileyPublished in: European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society (2022)
Our analysis considers the spine as a multi-segmental unit as opposed to a series of discrete and isolated spine segments. Integrative and multivariate approaches can be used to distill large and complex imaging datasets thereby improving the clinical utility of MRI-based biomarkers, and providing metrics for further analytical goals, including phenotyping.