Name
Title | ||
|---|---|---|
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network. |
Abstract | ||
|---|---|---|
Automated tissue characterization is one of the most crucial components of a computer aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research has been conducted in this field, the problem remains challenging. Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TMI.2016.2535865 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Lungs,Computed tomography,Diseases,Feature extraction,Convolution,Design automation,Neural networks | CAD,Computer vision,Convolutional neural network,Computer science,Honeycombing,Computer-aided diagnosis,Feature extraction,Artificial intelligence,Deep learning,Artificial neural network,Ground-glass opacity | Journal |
Volume | Issue | ISSN |
35 | 5 | 0278-0062 |
Citations | PageRank | References |
120 | 4.34 | 19 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marios Anthimopoulos | 1 | 247 | 13.75 |
| S Christodoulidis | 2 | 160 | 10.20 |
| Lukas Ebner | 3 | 136 | 5.78 |
| A Christe | 4 | 142 | 6.05 |
| Stavroula G Mougiakakou | 5 | 342 | 28.61 |