Work

Not without Context—A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by Experts

Year: 2023

Type: article

Source: Academic Radiology

DOI: 10.1016/j.acra.2023.10.019

Authors: Katharina V. Hoebel, Christopher P. Bridge, Albert Kim, Elizabeth R. Gerstner, Ina K. Ly, Francis Deng, Matthew N. DeSalvo, Jorg Dietrich, Raymond Huang, Susie Y. Huang, Stuart R. Pomerantz, Saivenkat Vagvala, Bruce R. Rosen, Jayashree Kalpathy-Cramer

Institutions: Harvard University, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts Institute of Technology, Center for Neuro-Oncology, Johns Hopkins University, Johns Hopkins Medicine, Brigham and Women's Hospital, University of Colorado Anschutz

Language: English

Topic: Brain Tumor Detection and Classification

Subfield: Neurology

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: closed

Funder: National Cancer Institute

Award: Distributed Learning of Deep Learning Models for Cancer Research

OpenAlex ID: W4388570334

FWCI: 0.513

Cites: 31

Cited by: 5

Related to: 10