11 citations · 13 across the 2 of their papers we have counts for
4 papers · 1 filter
MADGAN: unsupervised Medical Anomaly Detection GAN using multiple adjacent brain MRI slice reconstruction
Changhee Han, Leonardo Rundo, Kohei Murao +7
Unsupervised learning can discover various unseen abnormalities, relying on large-scale unannotated medical images of healthy subjects. Towards this, unsupervised methods reconstru…
Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems
Changhee Han, Leonardo Rundo, Kohei Murao +2
Despite the success of Convolutional Neural Network-based Computer-Aided Diagnosis research, its clinical applications remain challenging. Accordingly, developing medical Artificia…
Learning More with Less: GAN-based Medical Image Augmentation
Changhee Han, Kohei Murao, Shin'ichi Satoh +1
Convolutional Neural Network (CNN)-based accurate prediction typically requires large-scale annotated training data. In Medical Imaging, however, both obtaining medical data and an…
Learning More with Less: Conditional PGGAN-based Data Augmentation for Brain Metastases Detection Using Highly-Rough Annotation on MR Images
Changhee Han, Kohei Murao, Tomoyuki Noguchi +5
Accurate Computer-Assisted Diagnosis, associated with proper data wrangling, can alleviate the risk of overlooking the diagnosis in a clinical environment. Towards this, as a Data…