Extended nnU-Net for Brain Metastasis Detection and Segmentation in Contrast-Enhanced Magnetic Resonance Imaging With a Large Multi-Institutional Data Set-Reference-Cited by-同舟云学术

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Extended nnU-Net for Brain Metastasis Detection and Segmentation in Contrast-Enhanced Magnetic Resonance Imaging With a Large Multi-Institutional Data Set

Published:2024-07 Issue: Volume: Page:
ISSN:0360-3016
Container-title:International Journal of Radiation Oncology*Biology*Physics
language:en
Short-container-title:International Journal of Radiation Oncology*Biology*Physics

Author:

Yoo Youngjin^ORCID,Gibson Eli,Zhao Gengyan,Re Thomas J.,Parmar Hemant,Das Jyotipriya,Wang Hesheng,Kim Michelle M.,Shen Colette,Lee Yueh,Kondziolka Douglas,Ibrahim Mohannad,Lian Jun,Jain Rajan,Zhu Tong,Comaniciu Dorin,Balter James M.,Cao Yue

Funder

Amazon Web Services

National Institutes of Health

Publisher

Elsevier BV

Reference30 articles.

1. Epidemiology of synchronous brain metastases;Singh;NeuroOncol Adv,2020

2. Stereotactic radiosurgery for patients with multiple brain metastases (JLGK0901): a multi-institutional prospective observational study;Yamamoto;Lancet Oncol,2014

3. Automated detection and segmentation of brain metastases in stereotactic radiosurgery using three-dimensional deep neural networks;Lu;Int J Radiat Oncol Biol Phys,2019

4. Automated brain metastases segmentation with a deep dive into false-positive detection;Ziyaee;Adv Radiat Oncol,2023

5. Automated brain metastases detection framework for T1-weighted contrast-enhanced 3D MRI;Dikici;IEEE J Biomed Health Inform,2020

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