1 citations · 1 across the 4 of their papers we have counts for
3 papers · 1 filter
CADD: Context aware disease deviations via restoration of brain images using normative conditional diffusion models
Ana Lawry Aguila, Ayodeji Ijishakin, Juan Eugenio Iglesias +5
Applying machine learning to real-world medical data, e.g. from hospital archives, has the potential to revolutionize disease detection in brain images. However, detecting patholog…
X2CT-FLOW: Maximum a posteriori reconstruction using a progressive flow-based deep generative model for ultra sparse-view computed tomography in ultra low-dose protocols
Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura +4
Ultra sparse-view computed tomography (CT) algorithms can reduce radiation exposure of patients, but those algorithms lack an explicit cycle consistency loss minimization and an ex…
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…