Work

High-resolution 3D abdominal segmentation with random patch network fusion

Year: 2020

Type: article

Source: Medical Image Analysis

DOI: 10.1016/j.media.2020.101894

Authors: Yucheng Tang, Riqiang Gao, Ho Hin Lee, Shizhong Han, Yunqiang Chen, Dashan Gao, Vishwesh Nath, Camilo Bermudez, Michael R. Savona, Richard G. Abramson, Shunxing Bao, Ilwoo Lyu, Yuankai Huo, Bennett A. Landman

Institutions: Vanderbilt University, Sigma Technologies (United States), Vanderbilt University Medical Center

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Science Foundation, Vanderbilt Institute for Clinical and Translational Research, National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering, National Center for Advancing Translational Sciences

Awards: CAREER: Modeling Personalized Brain Development with Big Data, Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRI, The Vanderbilt Institute for Clinical and Translational Research (VICTR)

OpenAlex ID: W3112256294

FWCI: 2.909

Cites: 76

Cited by: 67

Related to: 10