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Feature Extraction and Classification of Digital Kidney Ultrasound Images: A Hybrid Approach

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Abstract

Ultrasound image is widely used medical imaging modality for the diagnosis of diseases. In this work, a novel hybrid approach for classification of diseased kidney medical ultrasound images is proposed. The segmented images are passed through the stage of feature extraction. Different features, namely, Haralick, shape, wavelet, Tamura, and histogram oriented gradient features are used for classification. The method focuses on recognizing the most dominant feature set that characterizes the texture of a stone, cyst or normal kidney ultrasound image. Extracted features are individually used for classification by three different classifiers namely k-nearest neighborhood, fuzzy k-nearest neighborhood, and support vector machine. The hybrid approach for feature extraction containing the combination of wavelet and shape features shows the optimal classification accuracy. The efficiency of the method is tested with performance parameters such as accuracy, sensitivity, and specificity. The results obtained show the efficiency of the proposed method.

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ACKNOWLEDGMENTS

Authors would like to thank Dr. Bhushita B. Lakhkar, Radiologist, BLDEDU’s Shri. B.M. Patil Medical College Hospital and Research Centre, Vijayapur for providing USG image set of kidney. Authors are also thankful to Dr. Vinay Kundaragi, Nephrologist, BLDEDU’s Shri. B.M. Patil Medical College Hospital and Research Centre, Vijayapur for rendering manual segmentation of images.

Funding

The work is financially supported by Vision Group of Science and Technology (VGST), Government of Karnataka under RGS/F scheme (GRD no. 729/2017-18).

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Authors and Affiliations

  1. Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning), BLDEA’s V. P. Dr. P.G. Halakatti College of Engineering and Technology, 586103, Vijayapur, Karnataka, India

    Sunanda Biradar & Prema T. Akkasaligar

  2. Department of Information Science and Engineering, BLDEA’s V. P. Dr. P.G. Halakatti College of Engineering and Technology, 586103, Vijayapur, Karnataka, India

    Sumangala Biradar

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  1. Sunanda Biradar
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  2. Prema T. Akkasaligar
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Correspondence to Sunanda Biradar, Prema T. Akkasaligar or Sumangala Biradar.

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This article is a completely original work of its authors; it has not been published before and will not be sent to other publications until the PRIA Editorial Board decides not to accept it for publication.

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The authors declare that they have no conflicts of interest.

Additional information

Dr. Sunanda Biradar is working as Assistant Professor in department of Computer Science and Engineering of College of Engineering and Technology, Vijayapur, Karnataka, India. She has completed her Bachelor of Engineering from Visvesvaraya Technological University Belagavi, Karnataka, India in the year 2002. M.Tech. (CSE) from Visvesvaraya Technological University, Belagavi, Karnataka, India in 2009 and PhD from Visvesvaraya Technological University, Belagavi, Karnataka, India in 2021. Her areas of interest are medical image processing and pattern recognition. She has more than 15 research publications in reputed and peer reviewed international journals, conference proceedings, and book chapters. She has also received research fund from Vision Group of Science and Technology (VGST), KBITS, Govt. of Karnataka and KSCST, Karnataka.

Prema T. Akkasaligar has completed her Bachelor of Engineering from Karnataka University Dharawad in the year 1995, ME (CSE) from Gulbarga University, Gulbarga in 1999 and PhD from Gulbarga University, Gulbarga in 2013. Currently, she is working as Professor in the Department of Computer Science and Engineering of BLDEA’s V.P. Dr. P.G.H. College of Engineering and Technology, Vijayapur, Karnataka, India. She has more than 35 research publications in reputed and peer reviewed international journals, conference proceedings, and book chapters. She is life member of Computer Society of India (CSI), The Institution of Engineers, India (IEI), Life Member of Indian Society for Technical Education (ISTE), and International Association of Computer Science and Information Technology (IACSIT), Singapore. She has also received research fund from KBITS, Govt. of Karnataka and FOSS scheme of VTU Belagavi, Karnataka. Her areas of interest are medical image processing and computer vision.

Mrs. Sumangala Biradar is working as Assistant Professor in department of Information Science and Engineering of College of Engineering and Technology, Vijayapur, Karnataka, India. She has completed her Bachelor of Engineering from Visvesvaraya Technological University Belagavi, Karnataka, India in the year 2002. M.Tech. (CSE) from Visvesvaraya Technological University, Belagavi, Karnataka, India in 2011 and PhD (pursuing). From Visvesvaraya Technological University, Belagavi, Karnataka, India. Her areas of interest are machine learning, information security, and cryptography. She has published papers in reputed and peer reviewed international journals and conference proceedings. She has also received research fund from Vision Group of Science and Technology (VGST), Karnataka.

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Sunanda Biradar, Akkasaligar, P.T. & Biradar, S. Feature Extraction and Classification of Digital Kidney Ultrasound Images: A Hybrid Approach. Pattern Recognit. Image Anal. 32, 363–372 (2022). https://doi.org/10.1134/S1054661822020043

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