作者
Sanne GM van Velzen, Nikolas Lessmann, Birgitta K Velthuis, Ingrid EM Bank, Desiree HJG van den Bongard, Tim Leiner, Pim A de Jong, Wouter B Veldhuis, Adolfo Correa, James G Terry, John Jeffrey Carr, Max A Viergever, Helena M Verkooijen, Ivana Išgum
发表日期
2020/4
期刊
Radiology
卷号
295
期号
1
页码范围
66-79
出版商
Radiological Society of North America
简介
Background
Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown.
Purpose
To evaluate the performance of a DL method for automatic calcium scoring across a wide range of CT examination types and to investigate whether the method can adapt to different types of CT examinations when representative images are added to the existing training data set.
Materials and Methods
The study included 7240 participants who underwent various types of nonenhanced CT examinations that included the heart: coronary artery calcium (CAC) scoring CT …
学术搜索中的文章
SGM van Velzen, N Lessmann, BK Velthuis, IEM Bank… - Radiology, 2020