“…Over the past decades, SSMs have found widespread application in characterizing population data sets’ variability and predicting new instances within that population ( Barratt, et al, 2008 ; Baka, et al, 2011 ; Aldieri, et al, 2020 ). In the field of orthopaedics, SSMs have been employed for many applications regarding the femur, since it is one of the most implanted districts within the skeleton ( Lindner, et al, 2013 ; Sarkalkan et al, 2014 ; Noussios, et al, 2019 ). More in detail, SSMs have been employed to automatize the segmentation of the femur from clinical images ( Bryan et al, 2010 ); to predict missing parts from portions of the distal femur ( Ramme, et al, 2011 ) or to predict more complex femoral shapes from incomplete or sparse data obtained through less invasive methods (e.g., DXA images) ( Humbert et al, 2017 ); to create new virtual instances ( Pascoletti, et al, 2021 ; La Mattina, et al, 2023 ); to classify subjects and identify diseases ( Waarsing, et al, 2010 ; Aldieri, et al, 2022 ).…”