11 citations · 22 across the 9 of their papers we have counts for
14 papers
BAPGAN: GAN-based Bone Age Progression of Femur and Phalange X-ray Images
Shinji Nakazawa, Changhee Han, Joe Hasei +2
Convolutional Neural Networks play a key role in bone age assessment for investigating endocrinology, genetic, and growth disorders under various modalities and body regions. Howev…
Pathology-Aware Generative Adversarial Networks for Medical Image Augmentation
Changhee Han
Convolutional Neural Networks (CNNs) can play a key role in Medical Image Analysis under large-scale annotated datasets. However, preparing such massive dataset is demanding. In th…
Effort-free Automated Skeletal Abnormality Detection of Rat Fetuses on Whole-body Micro-CT Scans
Akihiro Fukuda, Changhee Han, Kazumi Hakamada
Machine Learning-based fast and quantitative automated screening plays a key role in analyzing human bones on Computed Tomography (CT) scans. However, despite the requirement in dr…
Tips and Tricks to Improve CNN-based Chest X-ray Diagnosis: A Survey
Changhee Han, Takayuki Okamoto, Koichi Takeuchi +6
Convolutional Neural Networks (CNNs) intrinsically requires large-scale data whereas Chest X-Ray (CXR) images tend to be data/annotation-scarce, leading to over-fitting. Therefore,…
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…