A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Convolutional Neural Networks for Multi-scale Lung Nodule Classification in CT: Influence of Hyperparameter Tuning on Performance
2022
TEM Journal
In this study, a system based in Convolutional Neural Networks for differentiating lung nodules and non-nodules in Computed Tomography is developed. Multi-scale patches, extracted from LIDC-IDRI database, are used to train different CNN models. Adjustable hyperparameters are modified sequentially, to study their influence, evaluate learning process and find each size best performing network. Classification accuracies obtained are superior to 87% for all sizes with areas under Receiver Operating
doi:10.18421/tem111-37
fatcat:flurh5ne4jggden3vkutlsguby