Work

Texture analysis on conventional MRI images accurately predicts early malignant transformation of low-grade gliomas

Year: 2019

Type: article

Study design: Observational Study

Source: European Radiology

DOI: 10.1007/s00330-018-5921-1

Authors: Shun Zhang, Gloria Chia-Yi Chiang, Rajiv S. Magge, Howard Alan Fine, Rohan Ramakrishna, Eileen Wang Chang, Tejas Pulisetty, Yi Wang, Wenzhen Zhu, Ilhami Kovanlikaya

Institutions: Tongji Hospital, Weill Cornell Medicine, Huazhong University of Science and Technology, Saint Louis University, Cornell University

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

Funders: National Science Foundation, Foundation for the National Institutes of Health, National Natural Science Foundation of China

Awards: G2559222047, 缺血性脑卒中神经血管单元损伤与重塑的多模态影像学研究, G781119464, G8734269645, G8853064641

OpenAlex ID: W2909717355

FWCI: 2.548

Cites: 42

Cited by: 24

Related to: 10