3 papers
eess.IV2019
Adaptive Segmentation of Knee Radiographs for Selecting the Optimal ROI in Texture Analysis
Neslihan Bayramoglu, Aleksei Tiulpin, Jukka Hirvasniemi +2
The purposes of this study were to investigate: 1) the effect of placement of region-of-interest (ROI) for texture analysis of subchondral bone in knee radiographs, and 2) the abil…
physics.med-ph2019
Bone Texture Analysis for Prediction of Incident Radio-graphic Hip Osteoarthritis Using Machine Learning: Data from the Cohort Hip and Cohort Knee (CHECK) study
Jukka Hirvasniemi, Willem Paul Gielis, Saeed Arbabi +4
Our aim was to assess the ability of radiography-based bone texture parameters in proximal femur and acetabulum to predict incident radiographic hip osteoarthritis (rHOA) over a 10…
physics.med-ph2019
Bone Density and Texture from Minimally Post-Processed Knee Radiographs in Subjects with Knee Osteoarthritis
Jukka Hirvasniemi, Jaakko Niinimäki, Jérôme Thevenot +1
Plain radiography is the most common modality to assess the stage of osteoarthritis. Our aims were to assess the relationship of radiography-based bone density and texture between…