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Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network

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Main Authors: Nurfarhana Hazwani, Jusoh, Haniza, Yazid, Shafriza Nisha, Basah, Saufiah, Abdul Rahim
Other Authors: hanizayazid@unimap.edu.my
Format: Article
Language:English
Published: IOP Publishing 2020
Subjects:
Pulmonary nodule
Computed Tomography (CT)
Lung nodules diagnosis
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69014
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spelling my.unimap-690142020-12-16T02:48:36Z Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network Nurfarhana Hazwani, Jusoh Haniza, Yazid Shafriza Nisha, Basah Saufiah, Abdul Rahim hanizayazid@unimap.edu.my Pulmonary nodule Computed Tomography (CT) Lung nodules diagnosis Link to publisher's homepage at https://iopscience.iop.org/ This research aims to detect the pulmonary nodule presented in lung Computed Tomography (CT) scan images. Generally, a Computer-Aided Diagnostic (CAD) system was designed and developed to aid the radiologists in medical imaging department to reduce the time and to obtain faster and better results for lung nodules diagnosis of a patient. Four major stages involve in this paper which are pre-processing, segmentation, features extraction and classification. The images that were utilized were acquired from LIDC-IDRI database that available publicly for CT scan lung images. Initially, the median filter was employed in preprocessing to filter and remove the noises, unwanted distortions and artifacts presented in the images during scanning process. For the second stage, the implementation of Otsu thresholding (thresholding-based method) and watershed algorithm (region-based method) were used to segment the nodules (Region of Interest (ROI)). Manual cropping method was implemented to segment the nodule for further process. The main contribution of this paper is the extraction of the features based on shape descriptor. 10 features were extracted from the segmented nodules. Finally, all extracted features from the segmented nodules were classified into nodule candidates and non-nodule candidates using Back Propagation Neural Network (BPNN). Based on the experiment, it can be observed that the proposed approach works well with CT scan images and segmented the interested nodules with the accuracy of 94%. This semi-automated approach is fast compared with the conventional approach used by the radiologists in current time being. 2020-12-16T02:48:36Z 2020-12-16T02:48:36Z 2019 Article Journal of Physics: Conference Series, vol.1372, 2019, 6 pages 1742-6588 (print) 1742-6596 (online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69014 https://iopscience.iop.org/ en International Conference on Biomedical Engineering (ICoBE); IOP Publishing
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Pulmonary nodule
Computed Tomography (CT)
Lung nodules diagnosis
spellingShingle Pulmonary nodule
Computed Tomography (CT)
Lung nodules diagnosis
Nurfarhana Hazwani, Jusoh
Haniza, Yazid
Shafriza Nisha, Basah
Saufiah, Abdul Rahim
Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network
description Link to publisher's homepage at https://iopscience.iop.org/
author2 hanizayazid@unimap.edu.my
author_facet hanizayazid@unimap.edu.my
Nurfarhana Hazwani, Jusoh
Haniza, Yazid
Shafriza Nisha, Basah
Saufiah, Abdul Rahim
format Article
author Nurfarhana Hazwani, Jusoh
Haniza, Yazid
Shafriza Nisha, Basah
Saufiah, Abdul Rahim
author_sort Nurfarhana Hazwani, Jusoh
title Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network
title_short Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network
title_full Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network
title_fullStr Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network
title_full_unstemmed Detection of Pulmonary Nodule using Shape-Based Feature Descriptor and Neural Network
title_sort detection of pulmonary nodule using shape-based feature descriptor and neural network
publisher IOP Publishing
publishDate 2020
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69014
_version_ 1698698543817031680
score 13.160551

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