423 citations · 591 across the 12 of their papers we have counts for
12 papers
3D Graph Anatomy Geometry-Integrated Network for Pancreatic Mass Segmentation, Diagnosis, and Quantitative Patient Management
Tianyi Zhao, Kai Cao, Jiawen Yao +6
The pancreatic disease taxonomy includes ten types of masses (tumors or cysts)[20,8]. Previous work focuses on developing segmentation or classification methods only for certain ma…
DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Contrast-Enhanced CT Imaging
Jiawen Yao, Yu Shi, Le Lu +2
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and carries a dismal prognosis. Surgery remains the best chance of a potential cure for patients who are e…
Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-Institutional Multi-Phase Partially-Annotated CT Scans
Ling Zhang, Yu Shi, Jiawen Yao +5
Accurate and automated tumor segmentation is highly desired since it has the great potential to increase the efficiency and reproducibility of computing more complete tumor measure…
When Unseen Domain Generalization is Unnecessary? Rethinking Data Augmentation
Ling Zhang, Xiaosong Wang, Dong Yang +7
Recent advances in deep learning for medical image segmentation demonstrate expert-level accuracy. However, in clinically realistic environments, such methods have marginal perform…
Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data
Ling Zhang, Le Lu, Xiaosong Wang +4
Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment and surgical planning. Recent advances of co…
Fine-Grained Classification of Cervical Cells Using Morphological and Appearance Based Convolutional Neural Networks
Haoming Lin, Yuyang Hu, Siping Chen +2
Fine-grained classification of cervical cells into different abnormality levels is of great clinical importance but remains very challenging. Contrary to traditional classification…
DeepPap: Deep Convolutional Networks for Cervical Cell Classification
Ling Zhang, Le Lu, Isabella Nogues +3
Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into…
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
Zhihui Guo, Ling Zhang, Le Lu +4
This paper reports Deep LOGISMOS approach to 3D tumor segmentation by incorporating boundary information derived from deep contextual learning to LOGISMOS - layered optimal graph i…
Self-Learning to Detect and Segment Cysts in Lung CT Images without Manual Annotation
Ling Zhang, Vissagan Gopalakrishnan, Le Lu +3
Image segmentation is a fundamental problem in medical image analysis. In recent years, deep neural networks achieve impressive performances on many medical image segmentation task…
Convolutional Invasion and Expansion Networks for Tumor Growth Prediction
Ling Zhang, Le Lu, Ronald M. Summers +2
Tumor growth is associated with cell invasion and mass-effect, which are traditionally formulated by mathematical models, namely reaction-diffusion equations and biomechanics. Such…
Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database
Ke Yan, Xiaosong Wang, Le Lu +4
Radiologists in their daily work routinely find and annotate significant abnormalities on a large number of radiology images. Such abnormalities, or lesions, have collected over ye…
Personalized Pancreatic Tumor Growth Prediction via Group Learning
Ling Zhang, Le Lu, Ronald M. Summers +2
Tumor growth prediction, a highly challenging task, has long been viewed as a mathematical modeling problem, where the tumor growth pattern is personalized based on imaging and cli…