Deep Learning Based on MR Imaging for Predicting Outcome of Uterine Fibroid Embolization-Reference-Cited by-同舟云学术

Deep Learning Based on MR Imaging for Predicting Outcome of Uterine Fibroid Embolization

Published:2020-06 Issue:6 Volume:31 Page:1010-1017.e3
ISSN:1051-0443
Container-title:Journal of Vascular and Interventional Radiology
language:en
Short-container-title:Journal of Vascular and Interventional Radiology

Author:

Luo Yong-Heng,Xi Ianto Lin,Wang Robin,Abdallah Hatem Omar,Wu Jing,Vance Ansar Z.,Chang Ken,Kohi Maureen,Jones Lisa,Reddy Shilpa,Zhang Zi-Shu,Bai Harrison X.,Shlansky-Goldberg Richard

Funder

Radiological Society of North America

National Natural Science Foundation of China

Society of Interventional Radiology Foundation Radiology Resident Research

National Institutes of Health

National Institute of Biomedical Imaging and Bioengineering training

Publisher

Elsevier BV

Subject

Cardiology and Cardiovascular Medicine,Radiology Nuclear Medicine and imaging

Reference26 articles.

1. Uterine Fibroid Embolization;Young,2019

2. Leiomyoma volume changes at follow-up after uterine artery embolization: correlation with the initial leiomyoma volume and location;Naguib;J Vasc Interv Radiol,2010

3. Ineffectiveness of magnetic resonance imaging enhancement to predict fibroid volume reduction after uterine artery embolization;Bao;Proc (Bayl Univ Med Cent),2017

4. Magnetic resonance signal intensity ratio measurement before uterine artery embolization: ability to predict fibroid size reduction;Duvnjak;Cardiovasc Intervent Radiol,2017

5. Sample-Size determination methodologies for machine learning in medical imaging research: a systematic review;Balki;Can Assoc Radiol J,2019

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