Trained Generative and Classification Models from "Generating Synthetic Past and Future States of Knee Osteoarthritis Radiographs Using Cycle-Consistent Generative Adversarial Neural Networks

Name: Trained Generative and Classification Models from "Generating Synthetic Past and Future States of Knee Osteoarthritis Radiographs Using Cycle-Consistent Generative Adversarial Neural Networks
Creator: Fabi Prezja
Published: 2025-02-11T18:58:13.091Z
Keywords: Osteoarthritis, Synthetic Image, Deep Learning, Generative Adversarial Network

Prezja, Fabi; Annala, Leevi; Kiiskinen, Sampsa; Lahtinen, Suvi; Ojala, Timo; Nieminen, Paavo

doi:10.17632/rhs88fdrwg.1

Trained Generative and Classification Models from "Generating Synthetic Past and Future States of Knee Osteoarthritis Radiographs Using Cycle-Consistent Generative Adversarial Neural Networks

Published: 11 February 2025| Version 1 | DOI: 10.17632/rhs88fdrwg.1

Contributors:

Fabi Prezja, Leevi Annala, Sampsa Kiiskinen, Suvi Lahtinen, Timo Ojala, Paavo Nieminen

Description

This repository encompasses the fully trained Cycle-Consistent Generative Adversarial Neural Networks and the EfficientNetV2 Classification model from the paper "Generating Synthetic Past and Future States of Knee Osteoarthritis Radiographs Using Cycle-Consistent Generative Adversarial Neural Networks", published in Computers in Biology and Medicine (Elsevier) https://www.sciencedirect.com/science/article/pii/S0010482525001350. To load these models effectively, users must have TensorFlow/Keras installed and be running Python version 3.7 or higher.

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Please see: https://www.sciencedirect.com/science/article/pii/S0010482525001350

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Jyvaskylan Yliopisto

Trained Generative and Classification Models from "Generating Synthetic Past and Future States of Knee Osteoarthritis Radiographs Using Cycle-Consistent Generative Adversarial Neural Networks

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