233 citations · 240 across the 4 of their papers we have counts for
5 papers
Robust Medical Image Classification from Noisy Labeled Data with Global and Local Representation Guided Co-training
Cheng Xue, Lequan Yu, Pengfei Chen +2
Deep neural networks have achieved remarkable success in a wide variety of natural image and medical image computing tasks. However, these achievements indispensably rely on accura…
Cascaded Robust Learning at Imperfect Labels for Chest X-ray Segmentation
Cheng Xue, Qiao Deng, Xiaomeng Li +2
The superior performance of CNN on medical image analysis heavily depends on the annotation quality, such as the number of labeled image, the source of image, and the expert experi…
Global Guidance Network for Breast Lesion Segmentation in Ultrasound Images
Cheng Xue, Lei Zhu, Huazhu Fu +4
Automatic breast lesion segmentation in ultrasound helps to diagnose breast cancer, which is one of the dreadful diseases that affect women globally. Segmenting breast regions accu…
An Active Learning Approach for Reducing Annotation Cost in Skin Lesion Analysis
Xueying Shi, Qi Dou, Cheng Xue +3
Automated skin lesion analysis is very crucial in clinical practice, as skin cancer is among the most common human malignancy. Existing approaches with deep learning have achieved…
Robust Learning at Noisy Labeled Medical Images: Applied to Skin Lesion Classification
Cheng Xue, Qi Dou, Xueying Shi +2
Deep neural networks (DNNs) have achieved great success in a wide variety of medical image analysis tasks. However, these achievements indispensably rely on the accurately-annotate…