18 citations · 26 across the 5 of their papers we have counts for
5 papers
Landmark-free Assessment of Lower-limb Alignment with Implicit Neural Shape Functions from Knee Radiographs
Zhisen Hu, Antti Kemppainen, David Johnson +5
Radiographic assessment of lower-limb alignment (LLA) is important for predicting joint health and surgical outcomes in total knee arthroplasty. Traditional measurement methods are…
Toward Cost-efficient Adaptive Clinical Trials in Knee Osteoarthritis with Reinforcement Learning
Khanh Nguyen, Huy Hoang Nguyen, Egor Panfilov +1
Osteoarthritis (OA) is the most common musculoskeletal disease, with knee OA (KOA) being one of the leading causes of disability and a significant economic burden. Predicting KOA p…
End-To-End Prediction of Knee Osteoarthritis Progression With Multi-Modal Transformers
Egor Panfilov, Simo Saarakkala, Miika T. Nieminen +1
Knee Osteoarthritis (KOA) is a highly prevalent chronic musculoskeletal condition with no currently available treatment. The manifestation of KOA is heterogeneous and prediction of…
Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning
Egor Panfilov, Simo Saarakkala, Miika T. Nieminen +1
Accurate prediction of knee osteoarthritis (KOA) progression from structural MRI has a potential to enhance disease understanding and support clinical trials. Prior art focused on…
Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation
Egor Panfilov, Aleksei Tiulpin, Stefan Klein +2
Degeneration of articular cartilage (AC) is actively studied in knee osteoarthritis (OA) research via magnetic resonance imaging (MRI). Segmentation of AC tissues from MRI data is…