Regression to Classification: Ordinal Prediction of Calcified Vessels Using Customized ResNet50
Author:
Affiliation:
1. Department of Computer and Electronic Systems Engineering, Hankuk University of Foreign Studies, Yongin, South Korea
2. Department of Radiology, Seoul National University Bundang Hospital, Seongnam, South Korea
Funder
Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10108997.pdf?arnumber=10108997
Reference50 articles.
1. Detection of Arterial Calcification in Mammograms by Random Walks
2. Identification of breast vascular calcium deposition in digital mammography by linear structure analysis
3. Deep neural networks segment neuronal membranes in electron microscopy images;ciresan;Proc Adv Neural Inf Process Syst,2012
4. Prediction of subclinical coronary artery disease with breast arterial calcification and low bone mass in asymptomatic women;chun,2018
5. Automated Delineation of Calcified Vessels in Mammography by Tracking With Uncertainty and Graphical Linking Techniques
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