Randomized multi-reader evaluation of automated detection and segmentation of brain tumors in stereotactic radiosurgery with deep neural networks
Journal
Neuro-oncology
Journal Volume
23
Journal Issue
9
Date Issued
2021
Author(s)
Cheng, Yueh-Hung
Chang, Yu-Cheng
Lin, Jhih-Yuan
Liang, Chih-Hung
Lu, Jen-Tang
Abstract
Stereotactic radiosurgery (SRS), a validated treatment for brain tumors, requires accurate tumor contouring. This manual segmentation process is time-consuming and prone to substantial inter-practitioner variability. Artificial intelligence (AI) with deep neural networks have increasingly been proposed for use in lesion detection and segmentation but have seldom been validated in a clinical setting.
Subjects
artificial intelligence; brain tumor; deep learning; randomization; stereotactic radiosurgery
SDGs
Type
journal article