2023
DOI: 10.1007/s00330-023-09946-w
|View full text |Cite
|
Sign up to set email alerts
|

Efficacy of exponentiation method with a convolutional neural network for classifying lung nodules on CT images by malignancy level

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2025
2025

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(1 citation statement)
references
References 28 publications
0
1
0
Order By: Relevance
“…Despite the advantages of deep learning techniques in simplifying the procedure of lung nodule analysis, the accuracy of lung nodule classification still needs improvement. Takuma et al [ 14 ] evaluated the effectiveness of the exponentiation method for improving the performance of a CNN in the task of classifying lung nodules on CT images according to malignancy level. Experimental results improved accuracy of the CNN and the ability to adjust sensitivity and specificity by selecting the exponent value.…”
Section: Related Workmentioning
confidence: 99%
“…Despite the advantages of deep learning techniques in simplifying the procedure of lung nodule analysis, the accuracy of lung nodule classification still needs improvement. Takuma et al [ 14 ] evaluated the effectiveness of the exponentiation method for improving the performance of a CNN in the task of classifying lung nodules on CT images according to malignancy level. Experimental results improved accuracy of the CNN and the ability to adjust sensitivity and specificity by selecting the exponent value.…”
Section: Related Workmentioning
confidence: 99%