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arXiv · 2110.08509

BAPGAN: GAN-based Bone Age Progression of Femur and Phalange X-ray Images

Shinji Nakazawa·Changhee Han·Joe Hasei·Ryuichi Nakahara·Toshifumi Ozaki
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Abstract

Convolutional Neural Networks play a key role in bone age assessment for investigating endocrinology, genetic, and growth disorders under various modalities and body regions. However, no researcher has tackled bone age progression/regression despite its valuable potential applications: bone-related disease diagnosis, clinical knowledge acquisition, and museum education. Therefore, we propose Bone Age Progression Generative Adversarial Network (BAPGAN) to progress/regress both femur/phalange X-ray images while preserving identity and realism. We exhaustively confirm the BAPGAN's clinical potential via Frechet Inception Distance, Visual Turing Test by two expert orthopedists, and t-Distributed Stochastic Neighbor Embedding.

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Shinji Nakazawa, Changhee Han, Joe Hasei, Ryuichi Nakahara, Toshifumi Ozaki. 2021-10-16. BAPGAN: GAN-based Bone Age Progression of Femur and Phalange X-ray Images. https://arxiv.org/abs/2110.08509

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