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20172020
most citedDeepPap: Deep Convolutional Networks for Cervical Cell Classification

423 citations · 558 across the 9 of their papers we have counts for

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8 papers · 1 filter

cs.CV201940 cited

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…

cs.CV2019

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…

cs.CV2018

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…

cs.CV2018423 cited

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…

cs.CV201813 cited

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…

cs.CV20186 cited

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…