Active Sensing of Knee Osteoarthritis Progression with Reinforcement Learning

no code implementations • 5 Aug 2024 • Khanh Nguyen, Huy Hoang Nguyen, Egor Panfilov, Aleksei Tiulpin

Our approach is based on Reinforcement Learning (RL), and it leverages a novel reward function designed specifically for AS of disease progression in more than one part of a human body.

reinforcement-learning Reinforcement Learning +1

End-To-End Prediction of Knee Osteoarthritis Progression With Multi-Modal Transformers

no code implementations • 3 Jul 2023 • Egor Panfilov, Simo Saarakkala, Miika T. Nieminen, Aleksei Tiulpin

In this study, we leveraged recent advances in Deep Learning and, using a Transformer approach, developed a unified framework for the multi-modal fusion of knee imaging data.

Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning

1 code implementation • 26 Jan 2022 • Egor Panfilov, Simo Saarakkala, Miika T. Nieminen, Aleksei Tiulpin

Accurate prediction of knee osteoarthritis (KOA) progression from structural MRI has a potential to enhance disease understanding and support clinical trials.

Deep Learning

Improving Robustness of Deep Learning Based Knee MRI Segmentation: Mixup and Adversarial Domain Adaptation

1 code implementation • 12 Aug 2019 • Egor Panfilov, Aleksei Tiulpin, Stefan Klein, Miika T. Nieminen, Simo Saarakkala

Degeneration of articular cartilage (AC) is actively studied in knee osteoarthritis (OA) research via magnetic resonance imaging (MRI).

MRI segmentation Segmentation +1