Work

Semi-Automatic Segmentation of Prostate in CT Images via Coupled Feature Representation and Spatial-Constrained Transductive Lasso

Year: 2015

Type: article

Source: IEEE Transactions on Pattern Analysis and Machine Intelligence

DOI: 10.1109/tpami.2015.2424869

Authors: Yinghuan Shi, Yaozong Gao, Shu Liao, Daoqiang Zhang, Yang Gao, Dinggang Shen

Institutions: Nanjing University, University of North Carolina at Chapel Hill, Nanjing University of Aeronautics and Astronautics, Korea University

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: closed

Funders: National Science Foundation, National Natural Science Foundation of China, National Institutes of Health, National Cancer Institute

Awards: G2554420656, G3391680567, G4739438220, Online Collection of Patient-Specific Information for Daily Prostate Segmentation, 面向大数据的知识表示、推理、在线学习理论及应用研究, G567550234, G662034047, G6667581590, G7644015481

OpenAlex ID: W2161640927

FWCI: 2.888

Cites: 51

Cited by: 30

Related to: 10