You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Mendeley readers
Chapter title |
Neural Network Convolution (NNC) for Converting Ultra-Low-Dose to “Virtual” High-Dose CT Images
|
---|---|
Chapter number | 39 |
Book title |
Machine Learning in Medical Imaging
|
Published by |
Springer, Cham, September 2017
|
DOI | 10.1007/978-3-319-67389-9_39 |
Book ISBNs |
978-3-31-967388-2, 978-3-31-967389-9
|
Authors |
Kenji Suzuki, Junchi Liu, Amin Zarshenas, Toru Higaki, Wataru Fukumoto, Kazuo Awai, Suzuki, Kenji, Liu, Junchi, Zarshenas, Amin, Higaki, Toru, Fukumoto, Wataru, Awai, Kazuo |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 25 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 7 | 28% |
Student > Master | 6 | 24% |
Researcher | 3 | 12% |
Student > Bachelor | 2 | 8% |
Professor > Associate Professor | 2 | 8% |
Other | 1 | 4% |
Unknown | 4 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 10 | 40% |
Engineering | 5 | 20% |
Medicine and Dentistry | 1 | 4% |
Social Sciences | 1 | 4% |
Unknown | 8 | 32% |