Name
Title | ||
|---|---|---|
MR-Forest: A Deep Decision Framework for False Positive Reduction in Pulmonary Nodule Detection. |
Abstract | ||
|---|---|---|
With the development of deep learning methods such as convolutional neural network (CNN), the accuracy of automated pulmonary nodule detection has been greatly improved. However, the high computational and storage costs of the large-scale network have been a potential concern for the future widespread clinical application. In this paper, an alternative Multi-ringed (MR)-Forest framework, against t... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/JBHI.2019.2947506 | IEEE Journal of Biomedical and Health Informatics |
Keywords | DocType | Volume |
Feature extraction,Forestry,Three-dimensional displays,Harmonic analysis,Artificial neural networks,Task analysis,Computed tomography | Journal | 24 |
Issue | ISSN | Citations |
6 | 2168-2194 | 2 |
PageRank | References | Authors |
0.36 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongbo Zhu | 1 | 2 | 0.36 |
| Hai Zhao | 2 | 960 | 113.64 |
| Chunhe Song | 3 | 18 | 7.66 |
| Zijian Bian | 4 | 2 | 0.36 |
| Yuanguo Bi | 5 | 213 | 23.47 |
| Tong Liu | 6 | 2 | 0.36 |
| Xuan He | 7 | 2 | 1.04 |
| Dongxiang Yang | 8 | 2 | 0.70 |
| Wei Cai | 9 | 175 | 39.84 |