An Enhanced Texture-Based Feature Extraction Approach for Classification of Biomedical Images of CT-Scan of Lungs

被引：12

作者：

Srivastava, Varun ^{[1
]}

Gupta, Shilpa ^{[1
]}

Chaudhary, Gopal ^{[1
]}

Balodi, Arun ^{[2
]}

Khari, Manju ^{[3
]}

Garcia-Diaz, Vicente ^{[4
]}

机构：

[1] Bharati Vidyapeeths Coll Engn, New Delhi, India

[2] Atria Inst Technol, Bengaluru, Bengaluru, Karnataka, India

[3] Netaji Subhas Univ Technol, East Campus, Delhi, India

[4] Univ Oviedo, Dept Comp Sci, Oviedo, Spain

来源：

INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE | 2021年 / 6卷 / 07期

关键词：

Image Retrieval; Local Mesh Peak Valley Edge Patterns; Local Patterns; Bio-medical Image Classification; Texture-based Retrieval; TERNARY PATTERNS; BINARY PATTERNS; RETRIEVAL; DESCRIPTOR; MRI; EMPHYSEMA; EFFICIENT;

D O I：

10.9781/ijimai.2020.11.003

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Content Based Image Retrieval (CBIR) techniques based on texture have gained a lot of popularity in recent times. In the proposed work, a feature vector is obtained by concatenation of features extracted from local mesh peak valley edge pattern (LMePVEP) technique; a dynamic threshold based local mesh ternary pattern technique and texture of the image in five different directions. The concatenated feature vector is then used to classify images of two datasets viz. Emphysema dataset and Early Lung Cancer Action Program (ELCAP) lung database. The proposed framework has improved the accuracy by 12.56%, 9.71% and 7.01% in average for data set 1 and 9.37%, 8.99% and 7.63% in average for dataset 2 over three popular algorithms used for image retrieval.

引用

页码：18 / 25

页数：8

共 42 条

[1] Content-based image retrieval with compact deep convolutional features [J].

Alzu'bi, Ahmad ;

Amira, Abbes ;

Ramzan, Naeem .

NEUROCOMPUTING, 2017, 249 :95-105

[2]

[Anonymous], 2011, 2011 24 INT S COMPUT, DOI DOI 10.1109/CBMS.2011.5999142

[3] A novel local mesh color texture pattern for image retrieval system [J].

Charles, Yesubai Rubavathi ;

Ramraj, Ravi .

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 2016, 70 (03) :225-233

[4] Multiscale image segmentation using wavelet-domain hidden Markov models [J].

Choi, H ;

Baraniuk, RG .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (09) :1309-1321

[5] Local mesh ternary patterns: a new descriptor for MRI and CT biomedical image indexing and retrieval [J].

Deep, G. ;

Kaur, L. ;

Gupta, S. .

COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION, 2018, 6 (02) :155-169

[6] Directional local ternary quantized extrema pattern: A new descriptor for biomedical image indexing and retrieval [J].

Deep, G. ;

Kaur, L. ;

Gupta, S. .

ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2016, 19 (04) :1895-1909

[7] Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance [J].

Do, MN ;

Vetterli, M .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2002, 11 (02) :146-158

[8]

Eakins John, 1999, JISC TECHNOLOGY ED P

[9] Hybrid intelligent techniques for MRI brain images classification [J].

El-Dahshan, El-Sayed Ahmed ;

Hosny, Tamer ;

Salem, Abdel-Badeeh M. .

DIGITAL SIGNAL PROCESSING, 2010, 20 (02) :433-441

[10] A text based indexing system for mammographic image retrieval and classification [J].

Farruggia, Alfonso ;

Magro, Rosario ;

Vitabile, Salvatore .

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2014, 37 :243-251

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