624 citations · 997 across the 11 of their papers we have counts for
13 papers
Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classification
Yuan Xue, Jiarong Ye, Qianying Zhou +7
Histopathological analysis is the present gold standard for precancerous lesion diagnosis. The goal of automated histopathological classification from digital images requires super…
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…
SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos
Haomiao Ni, Yuan Xue, Qian Zhang +1
General movement assessment (GMA) of infant movement videos (IMVs) is an effective method for the early detection of cerebral palsy (CP) in infants. Automated body parsing is a cru…
Shape-Aware Organ Segmentation by Predicting Signed Distance Maps
Yuan Xue, Hui Tang, Zhi Qiao +6
In this work, we propose to resolve the issue existing in current deep learning based organ segmentation systems that they often produce results that do not capture the overall sha…
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…
Neural Wireframe Renderer: Learning Wireframe to Image Translations
Yuan Xue, Zihan Zhou, Xiaolei Huang
In architecture and computer-aided design, wireframes (i.e., line-based models) are widely used as basic 3D models for design evaluation and fast design iterations. However, unlike…
What Matters for Neural Cross-Lingual Named Entity Recognition: An Empirical Analysis
Xiaolei Huang, Jonathan May, Nanyun Peng
Building named entity recognition (NER) models for languages that do not have much training data is a challenging task. While recent work has shown promising results on cross-lingu…
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…
Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue
Yutao Ma, Tao Xu, Xiaolei Huang +10
Objective: Ultrahigh-resolution optical coherence microscopy (OCM) has recently demonstrated its potential for accurate diagnosis of human cervical diseases. One major challenge fo…
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
Tao Xu, Pengchuan Zhang, Qiuyuan Huang +4
In this paper, we propose an Attentional Generative Adversarial Network (AttnGAN) that allows attention-driven, multi-stage refinement for fine-grained text-to-image generation. Wi…
StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Han Zhang, Tao Xu, Hongsheng Li +4
Although Generative Adversarial Networks (GANs) have shown remarkable success in various tasks, they still face challenges in generating high quality images. In this paper, we prop…
SegAN: Adversarial Network with Multi-scale Loss for Medical Image Segmentation
Yuan Xue, Tao Xu, Han Zhang +2
Inspired by classic generative adversarial networks (GAN), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since…
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
Han Zhang, Tao Xu, Hongsheng Li +4
Synthesizing high-quality images from text descriptions is a challenging problem in computer vision and has many practical applications. Samples generated by existing text-to-image…