TELKOMNIKA Telecommunication, Computing, Electronics and Control
Cancerous lung nodule detection in computed tomography images
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Cancerous lung nodule detection in computed tomography images
Cancerous lung nodule detection in computed tomography images
Subject
Cancer detection, Computed tomography, Lung cancer, Texture features, Laplacian filter
Description
Diagnosis the computed tomography images (CT-images) is one of
the images that may take a lot of time in diagnosis by the radiologist and may miss some of cancerous nodules in these images. Therefore, in this paper a new novel enhancement and detection cancerous nodule algorithm is proposed to diagnose a CT-images. The novel algorithm is divided into three main stages. In first stage, suspicious regions are enhanced using modified LoG algorithm. Then in stage two, a potential cancerous nodule was detected based on visual appearance in lung. Finally, five texture features analysis algorithm is implemented to reduce number of detected FP regions. This algorithm is evaluated using 60 cases (normal and cancerous cases), and it shows a high sensitivity in detecting the cancerous lung nodules with TP ration 97% and with FP ratio 25 cluster/image.
the images that may take a lot of time in diagnosis by the radiologist and may miss some of cancerous nodules in these images. Therefore, in this paper a new novel enhancement and detection cancerous nodule algorithm is proposed to diagnose a CT-images. The novel algorithm is divided into three main stages. In first stage, suspicious regions are enhanced using modified LoG algorithm. Then in stage two, a potential cancerous nodule was detected based on visual appearance in lung. Finally, five texture features analysis algorithm is implemented to reduce number of detected FP regions. This algorithm is evaluated using 60 cases (normal and cancerous cases), and it shows a high sensitivity in detecting the cancerous lung nodules with TP ration 97% and with FP ratio 25 cluster/image.
Creator
Ayman Abu Baker, Yazeed Ghadi
Source
DOI: 10.12928/TELKOMNIKA.v18i5.15523
Publisher
Universitas Ahmad Dahlan
Date
October 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Ayman Abu Baker, Yazeed Ghadi , “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Cancerous lung nodule detection in computed tomography images,” Repository Horizon University Indonesia, accessed March 10, 2025, https://repository.horizon.ac.id/items/show/4086.
Cancerous lung nodule detection in computed tomography images,” Repository Horizon University Indonesia, accessed March 10, 2025, https://repository.horizon.ac.id/items/show/4086.