21 citations · 28 across the 6 of their papers we have counts for
6 papers
Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation
Hao Jiang, Cheng Jin, Huangjing Lin +15
Cervical cancer is a leading malignancy in female reproductive system. While AI-assisted cytology offers a cost-effective and non-invasive screening solution, current systems strug…
Deep Rib Fracture Instance Segmentation and Classification from CT on the RibFrac Challenge
Jiancheng Yang, Rui Shi, Liang Jin +22
Rib fractures are a common and potentially severe injury that can be challenging and labor-intensive to detect in CT scans. While there have been efforts to address this field, the…
Deep Omni-supervised Learning for Rib Fracture Detection from Chest Radiology Images
Zhizhong Chai, Luyang Luo, Huangjing Lin +2
Deep learning (DL)-based rib fracture detection has shown promise of playing an important role in preventing mortality and improving patient outcome. Normally, developing DL-based…
ORF-Net: Deep Omni-supervised Rib Fracture Detection from Chest CT Scans
Zhizhong Chai, Huangjing Lin, Luyang Luo +2
Most of the existing object detection works are based on the bounding box annotation: each object has a precise annotated box. However, for rib fractures, the bounding box annotati…
Conquering Data Variations in Resolution: A Slice-Aware Multi-Branch Decoder Network
Shuxin Wang, Shilei Cao, Zhizhong Chai +4
Fully convolutional neural networks have made promising progress in joint liver and liver tumor segmentation. Instead of following the debates over 2D versus 3D networks (for examp…
Deep Semi-supervised Metric Learning with Dual Alignment for Cervical Cancer Cell Detection
Zhizhong Chai, Luyang Luo, Huangjing Lin +3
Deep learning has achieved unprecedented success in various object detection tasks with huge amounts of labeled data. However, obtaining large-scale annotations for medical images…