140 citations · 179 across the 13 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.CV2019★ 4 cited
Selective Synthetic Augmentation with Quality Assurance
Yuan Xue, Jiarong Ye, Rodney Long +3
Supervised training of an automated medical image analysis system often requires a large amount of expert annotations that are hard to collect. Moreover, the proportions of data av…
eess.IV2019★ 6 cited
Comparing Deep Learning Models for Multi-cell Classification in Liquid-based Cervical Cytology Images
Sudhir Sornapudi, G. T. Brown, Zhiyun Xue +3
Liquid-based cytology (LBC) is a reliable automated technique for the screening of Papanicolaou (Pap) smear data. It is an effective technique for collecting a majority of the cerv…
eess.IV2019★ 6 cited
Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification
Yuan Xue, Qianying Zhou, Jiarong Ye +5
Cervical intraepithelial neoplasia (CIN) grade of histopathology images is a crucial indicator in cervical biopsy results. Accurate CIN grading of epithelium regions helps patholog…