Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss
Early detection and classification of pulmonary nodules using computer-aided diagnosis (CAD) systems is useful in reducing mortality rates of lung cancer. In this paper, we propose a new deep learning method to improve classification accuracy of pulmonary nodules in computed tomography (CT) scans. O...
Main Authors: | Giang Son Tran, Thi Phuong Nghiem, Van Thi Nguyen, Chi Mai Luong, Jean-Christophe Burie |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2019-01-01
|
Series: | Journal of Healthcare Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/5156416 |
Similar Items
-
Lung Nodule Classification via Deep Learning
by: Yi-Hua Chang, et al.
Published: (2014) -
Classification of Lung Nodule Using Hybridized Deep Feature Technique
by: Malin Bruntha, et al.
Published: (2020-12-01) -
Feature Representation Using Deep Autoencoder for Lung Nodule Image Classification
by: Keming Mao, et al.
Published: (2018-01-01) -
Classification of Lung Nodules Based on Deep Residual Networks and Migration Learning
by: Panpan Wu, et al.
Published: (2020-01-01) -
Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images
by: QingZeng Song, et al.
Published: (2017-01-01)