Open Access
ARTICLE
A Hybrid Approach for the Lung(s) Nodule Detection Using the Deformable Model and Distance Transform
Ayyaz Hussain1, Mohammed Alawairdhi2, Fayez Alazemi3, Sajid Ali Khan4, Muhammad Ramzan2,*
1 Department of Computer Science, Quaid e Azam University, Islamabad, 44000, Pakistan
2 College of Computing and Informatics, Saudi Electronic University, Riyadh, 11673, Saudi Arabia
3 Public Authority for Applied Education and Training, 6500, Kuwait
4 Department of Software Engineering, Foundation University Islamabad, Islamabad, 44000, Pakistan
* Corresponding Author: Muhammad Ramzan. Email:
Intelligent Automation & Soft Computing 2020, 26(5), 857-871. https://doi.org/10.32604/iasc.2020.010120
Abstract
The Computer Aided Diagnosis (CAD) systems are gaining more
recognition and being used as an aid by clinicians for detection and interpretation
of diseases every passing day due to their increasing accuracy and reliability. The
lung(s) nodule detection is a very crucial and difficult step for CAD systems. In
this paper, a hybrid approach for the lung nodule detection using a deformable
model and distance transform has been proposed. The proposed method has the
ability to detect all major kinds of nodules such as the juxta-plueral, isolated, and
the juxta-vescular, along with the non-solid nodules automatically and
intelligently. Results show an impressive 95.2% accuracy with 4.85 false positives
per scan. One significant achievement of the proposed work is its ability to detect
various sizes of nodules from 3 mm to 30 mm. The proposed technique has been
tested on the publicly available Lung(s) Image Database Consortium (LIDC). The
results clearly show the effectiveness of the proposed technique in early detection
with impressive accuracy.
Keywords
Cite This Article
APA Style
Hussain, A., Alawairdhi, M., Alazemi, F., Khan, S.A., Ramzan, M. (2020). A hybrid approach for the lung(s) nodule detection using the deformable model and distance transform. Intelligent Automation & Soft Computing, 26(5), 857-871. https://doi.org/10.32604/iasc.2020.010120
Vancouver Style
Hussain A, Alawairdhi M, Alazemi F, Khan SA, Ramzan M. A hybrid approach for the lung(s) nodule detection using the deformable model and distance transform. Intell Automat Soft Comput . 2020;26(5):857-871 https://doi.org/10.32604/iasc.2020.010120
IEEE Style
A. Hussain, M. Alawairdhi, F. Alazemi, S.A. Khan, and M. Ramzan "A Hybrid Approach for the Lung(s) Nodule Detection Using the Deformable Model and Distance Transform," Intell. Automat. Soft Comput. , vol. 26, no. 5, pp. 857-871. 2020. https://doi.org/10.32604/iasc.2020.010120