88 citations · 178 across the 5 of their papers we have counts for
5 papers
DSAL: Deeply Supervised Active Learning from Strong and Weak Labelers for Biomedical Image Segmentation
Ziyuan Zhao, Zeng Zeng, Kaixin Xu +2
Image segmentation is one of the most essential biomedical image processing problems for different imaging modalities, including microscopy and X-ray in the Internet-of-Medical-Thi…
A Hierarchical Deep Convolutional Neural Network and Gated Recurrent Unit Framework for Structural Damage Detection
Jianxi Yang, Likai Zhang, Cen Chen +5
Structural damage detection has become an interdisciplinary area of interest for various engineering fields, while the available damage detection methods are being in the process o…
A Deep Framework for Bone Age Assessment based on Finger Joint Localization
Xiaoman Zhang, Ziyuan Zhao, Cen Chen +6
Bone age assessment is an important clinical trial to measure skeletal child maturity and diagnose of growth disorders. Conventional approaches such as the Tanner-Whitehouse (TW) a…
Semi-Supervised Self-Taught Deep Learning for Finger Bones Segmentation
Ziyuan Zhao, Xiaoman Zhang, Cen Chen +6
Segmentation stands at the forefront of many high-level vision tasks. In this study, we focus on segmenting finger bones within a newly introduced semi-supervised self-taught deep…
Deep Learning for Lung Cancer Detection: Tackling the Kaggle Data Science Bowl 2017 Challenge
Kingsley Kuan, Mathieu Ravaut, Gaurav Manek +7
We present a deep learning framework for computer-aided lung cancer diagnosis. Our multi-stage framework detects nodules in 3D lung CAT scans, determines if each nodule is malignan…