2 citations · 3 across the 4 of their papers we have counts for
4 papers
Local Differential Privacy Image Generation Using Flow-based Deep Generative Models
Hisaichi Shibata, Shouhei Hanaoka, Yang Cao +5
Diagnostic radiologists need artificial intelligence (AI) for medical imaging, but access to medical images required for training in AI has become increasingly restrictive. To rele…
Aging prediction using deep generative model toward the development of preventive medicine
Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura +2
From birth to death, we all experience surprisingly ubiquitous changes over time due to aging. If we can predict aging in the digital domain, that is, the digital twin of the human…
Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection
Takahiro Suzuki, Shouhei Hanaoka, Issei Sato
A computer-aided detection (CAD) system based on machine learning is expected to assist radiologists in making a diagnosis. It is desirable to build CAD systems for the various typ…
A versatile anomaly detection method for medical images with a flow-based generative model in semi-supervision setting
H. Shibata, S. Hanaoka, Y. Nomura +5
Oversight in medical images is a crucial problem, and timely reporting of medical images is desired. Therefore, an all-purpose anomaly detection method that can detect virtually al…