20 citations · 58 across the 5 of their papers we have counts for
7 papers
3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes
Siqi Liu, Daguang Xu, S. Kevin Zhou +7
While deep convolutional neural networks (CNN) have been successfully applied for 2D image analysis, it is still challenging to apply them to 3D anisotropic volumes, especially whe…
Automatic Liver Segmentation Using an Adversarial Image-to-Image Network
Dong Yang, Daguang Xu, S. Kevin Zhou +5
Automatic liver segmentation in 3D medical images is essential in many clinical applications, such as pathological diagnosis of hepatic diseases, surgical planning, and postoperati…
Automatic Vertebra Labeling in Large-Scale 3D CT using Deep Image-to-Image Network with Message Passing and Sparsity Regularization
Dong Yang, Tao Xiong, Daguang Xu +10
Automatic localization and labeling of vertebra in 3D medical images plays an important role in many clinical tasks, including pathological diagnosis, surgical planning and postope…
A Fully-Automated Pipeline for Detection and Segmentation of Liver Lesions and Pathological Lymph Nodes
Assaf Hoogi, John W. Lambert, Yefeng Zheng +2
We propose a fully-automated method for accurate and robust detection and segmentation of potentially cancerous lesions found in the liver and in lymph nodes. The process is perfor…
Shaping the Future through Innovations: From Medical Imaging to Precision Medicine
Dorin Comaniciu, Klaus Engel, Bogdan Georgescu +1
Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information rep…
A Self-Taught Artificial Agent for Multi-Physics Computational Model Personalization
Dominik Neumann, Tommaso Mansi, Lucian Itu +10
Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust…