activity
20162020
most citedDeepPap: Deep Convolutional Networks for Cervical Cell Classification

423 citations · 485 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2020

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…

cs.CV2018★ 423 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.CV2017★ 7 cited

Unsupervised Joint Mining of Deep Features and Image Labels for Large-scale Radiology Image Categorization and Scene Recognition

Xiaosong Wang, Le Lu, Hoo-chang Shin +5

The recent rapid and tremendous success of deep convolutional neural networks (CNN) on many challenging computer vision tasks largely derives from the accessibility of the well-ann…

cs.CV2016★ 11 cited

Unsupervised Category Discovery via Looped Deep Pseudo-Task Optimization Using a Large Scale Radiology Image Database

Xiaosong Wang, Le Lu, Hoo-chang Shin +4

Obtaining semantic labels on a large scale radiology image database (215,786 key images from 61,845 unique patients) is a prerequisite yet bottleneck to train highly effective deep…

cs.CV2016★ 44 cited

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

Hoo-Chang Shin, Holger R. Roth, Mingchen Gao +6

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and the revival of deep CNN. CNNs enable learning data-d…