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Dataset Information

Development and Validation of a Deep Learning Model for Brain Tumor Diagnosis and Classification Using Magnetic Resonance Imaging.


ABSTRACT:

Importance

Deep learning may be able to use patient magnetic resonance imaging (MRI) data to aid in brain tumor classification and diagnosis.

Objective

To develop and clinically validate a deep learning system for automated identification and classification of 18 types of brain tumors from patient MRI data.

Design, setting, and participants

This diagnostic study was conducted using MRI data collected between 2000 and 2019 from 37 871 patients. A deep learning system for segmentation and classification of 18 types of intracranial tumors based on T1- and T2-weighted images and T2 contrast MRI sequences was developed and tested. The diagnostic accuracy of the system was tested using 1 internal and 3 external independent data sets. The clinical value of the system was ass

SUBMITTER: Gao P 

PROVIDER: S-EPMC9361083 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature