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Light Deep Model for Pulmonary Nodule Detection from CT Scan Images for Mobile Devices
Joint Authors
Cheikhrouhou, Omar
Masud, Mehedi
Muhammad, Ghulam
Hossain, M. Shamim
Alhumyani, Hesham
Alshamrani, Sultan S.
Ibrahim, Saleh
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-03
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
The emergence of cognitive computing and big data analytics revolutionize the healthcare domain, more specifically in detecting cancer.
Lung cancer is one of the major reasons for death worldwide.
The pulmonary nodules in the lung can be cancerous after development.
Early detection of the pulmonary nodules can lead to early treatment and a significant reduction of death.
In this paper, we proposed an end-to-end convolutional neural network- (CNN-) based automatic pulmonary nodule detection and classification system.
The proposed CNN architecture has only four convolutional layers and is, therefore, light in nature.
Each convolutional layer consists of two consecutive convolutional blocks, a connector convolutional block, nonlinear activation functions after each block, and a pooling block.
The experiments are carried out using the Lung Image Database Consortium (LIDC) database.
From the LIDC database, 1279 sample images are selected of which 569 are noncancerous, 278 are benign, and the rest are malignant.
The proposed system achieved 97.9% accuracy.
Compared to other famous CNN architecture, the proposed architecture has much lesser flops and parameters and is thereby suitable for real-time medical image analysis.
American Psychological Association (APA)
Masud, Mehedi& Muhammad, Ghulam& Hossain, M. Shamim& Alhumyani, Hesham& Alshamrani, Sultan S.& Cheikhrouhou, Omar…[et al.]. 2020. Light Deep Model for Pulmonary Nodule Detection from CT Scan Images for Mobile Devices. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1214919
Modern Language Association (MLA)
Masud, Mehedi…[et al.]. Light Deep Model for Pulmonary Nodule Detection from CT Scan Images for Mobile Devices. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1214919
American Medical Association (AMA)
Masud, Mehedi& Muhammad, Ghulam& Hossain, M. Shamim& Alhumyani, Hesham& Alshamrani, Sultan S.& Cheikhrouhou, Omar…[et al.]. Light Deep Model for Pulmonary Nodule Detection from CT Scan Images for Mobile Devices. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1214919
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214919