Comparative analysis of segmentation techniques based on chest X-ray images

被引:1
|
作者
Kiran, Mehreen [1 ]
Ahmed, Imran [1 ]
Khan, Nazish [1 ]
Rehman, Hamood Ur [1 ]
Din, Sadia [2 ]
Paul, Anand [2 ]
Reddy, Alavalapati Goutham [3 ]
机构
[1] Ctr Excellence Informat Technol, Inst Management Sci, Peshawar, Pakistan
[2] Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu, South Korea
[3] Natl Inst Technol, Dept Comp Sci & Engn, Tadepalligudem, Andhra Pradesh, India
关键词
Chest radiography; Survey; Computer-aided diagnosis; Codes; executable; Commands; Lung region extraction; Segmentation; MEANS CLUSTERING-ALGORITHM; CONTRAST ENHANCEMENT; K-MEANS; HISTOGRAM EQUALIZATION;
D O I
10.1007/s11042-019-7348-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The image segmentation is the basic step in the image processing involved in the processing of medical images. Over the past two decades, medical image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in research studies. This article surveys the techniques and their effect on chest X-ray images. The objective of this work is to study the key similarities and differences among the different published methods while highlighting their strengths and weaknesses on chest X-ray images. The reason is to assist the researchers in the choice of an appropriate lung segmentation methodology. We additionally give a complete portrayal of the existing few basic methods when combined with preprocessing method that can be utilized as a part of the segmentation. A discussion and fair analysis justified with experimental results along with quantitative correlation of the outcomes on 247 images of JSRT through Dice coefficient exhibited.
引用
收藏
页码:8483 / 8518
页数:36
相关论文
共 50 条
  • [1] Comparative analysis of segmentation techniques based on chest X-ray images
    Mahreen Kiran
    Imran Ahmed
    Nazish Khan
    Hamood ur Rehman
    Sadia Din
    Anand Paul
    Alavalapati Goutham Reddy
    Multimedia Tools and Applications, 2020, 79 : 8483 - 8518
  • [2] Deep Convolutional Neural Network with Segmentation Techniques for Chest X-Ray Analysis
    Wang, Binquan
    Wu, Zeyuan
    Khan, Zakir Ullah
    Liu, Chenglin
    Zhu, Ming
    PROCEEDINGS OF THE 2019 14TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2019), 2019, : 1212 - 1216
  • [3] Chest X-Ray Analysis of Tuberculosis by Deep Learning with Segmentation and Augmentation
    Stirenko, Sergii
    Kochura, Yuriy
    Alienin, Oleg
    Rokovyi, Oleksandr
    Gordienko, Yuri
    Gang, Peng
    Zeng, Wei
    2018 IEEE 38TH INTERNATIONAL CONFERENCE ON ELECTRONICS AND NANOTECHNOLOGY (ELNANO), 2018, : 422 - 428
  • [4] Weakly-Supervised Segmentation for Disease Localization in Chest X-Ray Images
    Viniavskyi, Ostap
    Dobko, Mariia
    Dobosevych, Oles
    ARTIFICIAL INTELLIGENCE IN MEDICINE (AIME 2020), 2020, : 249 - 259
  • [5] A deep unsupervised saliency model for lung segmentation in chest X-ray images
    de Almeida, Pedro Aurelio Coelho
    Borges, Dibio Leandro
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2023, 86
  • [6] Segmentation of Chest X-Ray Images Using U-Net Model
    Hashem S.A.
    Kamil M.Y.
    Mendel, 2022, 28 (02): : 49 - 53
  • [7] Chest X-ray segmentation using Sauvola thresholding and Gaussian derivatives responses
    Kiran, Mahreen
    Ahmed, Imran
    Khan, Nazish
    Reddy, Alavalapati Goutham
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2019, 10 (10) : 4179 - 4195
  • [8] Chest X-ray segmentation using Sauvola thresholding and Gaussian derivatives responses
    Mahreen Kiran
    Imran Ahmed
    Nazish Khan
    Alavalapati Goutham Reddy
    Journal of Ambient Intelligence and Humanized Computing, 2019, 10 : 4179 - 4195
  • [9] Customized Hybrid Level Sets for Automatic Lung Segmentation in Chest X-ray Images
    Kamalakannan, S.
    Antani, S.
    Long, R.
    Thoma, G.
    MEDICAL IMAGING 2013: IMAGE PROCESSING, 2013, 8669
  • [10] COVID-19 Detection from Chest X-ray Images Based on Deep Learning Techniques
    Mathesul, Shubham
    Swain, Debabrata
    Satapathy, Santosh Kumar
    Rambhad, Ayush
    Acharya, Biswaranjan
    Gerogiannis, Vassilis C.
    Kanavos, Andreas
    ALGORITHMS, 2023, 16 (10)