Work

Head and neck cancer patient images for determining auto‐segmentation accuracy in T2‐weighted magnetic resonance imaging through expert manual segmentations

Year: 2020

Type: article

Source: Medical Physics

DOI: 10.1002/mp.14803

Authors: Carlos E. Cardenas, Abdallah S. R. Mohamed, Jinzhong Yang, Mark Gooding, Harini Veeraraghavan, Jayashree Kalpathy-Cramer, Sweet Ping Ng, Yao Ding, Jihong Wang, Stephen Y. Lai, Clifton D. Fuller, Greg Sharp

Institutions: The University of Texas MD Anderson Cancer Center, The University of Texas Health Science Center at Houston, Mirada Medical (United Kingdom), Memorial Sloan Kettering Cancer Center, Harvard University, Massachusetts General Hospital, Peter MacCallum Cancer Centre

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

OpenAlex ID: W4250103036

FWCI:

Cites:

Cited by:

Related to: 10