10 citations · 25 across the 5 of their papers we have counts for
7 papers
Deep Cervix Model Development from Heterogeneous and Partially Labeled Image Datasets
Anabik Pal, Zhiyun Xue, Sameer Antani
Cervical cancer is the fourth most common cancer in women worldwide. The availability of a robust automated cervical image classification system can augment the clinical care provi…
Region Comparison Network for Interpretable Few-shot Image Classification
Zhiyu Xue, Lixin Duan, Wen Li +2
While deep learning has been successfully applied to many real-world computer vision tasks, training robust classifiers usually requires a large amount of well-labeled data. Howeve…
Synthetic Sample Selection via Reinforcement Learning
Jiarong Ye, Yuan Xue, L. Rodney Long +4
Synthesizing realistic medical images provides a feasible solution to the shortage of training data in deep learning based medical image recognition systems. However, the quality c…
Feature based Sequential Classifier with Attention Mechanism
Sudhir Sornapudi, R. Joe Stanley, William V. Stoecker +5
Cervical cancer is one of the deadliest cancers affecting women globally. Cervical intraepithelial neoplasia (CIN) assessment using histopathological examination of cervical biopsy…
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…
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…