Visual Geometry Group based on U-Shaped Model for Liver/Liver Tumor Segmentation

Authors

Keywords:

Convolutional Neural Network, Segmentation, Datasets, Liver

Abstract

Liver cancer is the primary reason of death around the globe. Manually detecting the infected tissues is a challenging and time-consuming task. The computerized methods help make accurate decisions and therapy processes. The segmentation accuracy might be increased to reduce the loss rate. Semantic segmentation performs a vital role in infected liver region segmentation. This article proposes a method that consists of two major steps; first, the local Laplacian filter is applied to improve the image quality. The second is the proposed semantic segmentation model in which features are extracted to the pre-trained VGG16 model and passed to the U-shaped network. This model consists of 51 layers: input, 23 convolutional, 4 max pooling, 4 transpose convolutional, 4 concatenated, 8 activation, and 7 batch-normalization. The proposed segmentation framework is trained on the selected hyperparameters that reduce the loss rate and increase the segmentation accuracy. The proposed approach more precisely segments the infected liver region. The proposed approach performance is accessed on two datasets such as 3DIRCADB and LiTS17. The proposed framework provides an average dice score of 0.98, which is far better compared to the existing works.

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Author Biographies

Javaria Amin, University of Wah

Javeria Amin currently serves as an Assistant Professor in the Department of Computer Science, University of Wah. She is a computer vision expert. Her research focuses on anomaly detection in various parts of the human body with the help of machine learning, deep learning, and quantum computing algorithms. She is also the chief Editor of UWCS Journal and guest editor and reviewer for numerous well-reputed computer science journals. Her research work published in different international journals have a cumulative impact factor of 200+ with over 1000 citations.

Muhammad Almas Anjum, National University of Technology (NUTECH)

Muhammad Almas Anjum is currently serving as Dean of University at National University of Technology (NUTECH), Pakistan. His areas of specialization are pattern recognition, security systems (biometrics), and computer vision. Apart of his more than 100 international publications in his area of specialization, he is the author of a book titled Face Recognition a Challenge in Biometrics: Image Resolution Issues in Face Recognition. He led the team for establishing Center of Excellence Information Technology, College of Electrical & Mechanical Engineering, and has served as its first pioneer head. He also designed and established a Center of Innovation and Entrepreneurship, College of Electrical and Mechanical Engineering. He has also served as the Dean for the Faculty of Computer Sciences, University of Wah, and the Director of Research and Development for the College of Electrical and Mechanical Engineering, NUST.

Muhammad Sharif, COMSATS University Islamabad

Muhammad Sharif, Ph.D. (Senior Member IEEE) is Associate Professor at COMSATS University Islamabad, Wah Campus Pakistan. He worked for one year in Alpha Soft UK-based software house in 1995. He is OCP in the Developer Track. He is in the teaching profession since 1996 to date. His research interests are Medical Imaging, Biometrics, Computer Vision, Machine Learning, and Agriculture Plants. He is being awarded COMSATS Research Productivity Award from 2011-2017. He served in TPC for IEEE FIT 2014-19 and currently serving as Associate Editor for IEEE Access, Guest Editor of Special Issues, and reviewer for well-reputed journals. He also headed the department from 2008 to 2011 and achieved the targeted outputs. He has more than 285+ research publications in IF, SCI, and ISI journals as well as in national and international conferences, and obtained 550+ Impact Factor. He has supervised/co-supervised 10 Ph.D. (CS) and 90+ MS (CS) theses to date.

Seifedine Kadry, Noroff University College

Seifedine Kadry received the bachelor’s degree from Lebanese University, in 1999, the M.S. degree from the University of Reims, France, and the EPFL, Lausanne, in 2002, the Ph.D. degree from Blaise Pascal University, France, in 2007, and the H.D.R. degree from the University of Rouen Normandy, in 2017. He is currently a Full Professor of data science with the Noroff University College, Norway. He is also an ABET Program Evaluator of computing and an ABET Program Evaluator of engineering technology. His current research interests include data science, education using technology, system prognostics, stochastic systems, and probability and reliability analysis.

Ruben González Crespo, Universidad Internacional de La Rioja

Rubén González Crespo is a full professor in Computer Science and Artificial Intelligence. Currently he is Vice-Rector of Academic Affairs in the Universidad Internacional de La Rioja. He is also EiC and associate editor in several indexed journals. His main research areas are Artificial Intelligence, Accessibility and Project Management. He has published more than 250 scientific publications and managed several research projects. He is an advisory board member for the Ministry of Education in Colombia and Spain Mr. Author’s awards and honors include the Frew Fellowship (Australian Academy of Science), the I. I. Rabi Prize (APS), the European Frequency and Time Forum Award, the Carl Zeiss Research Award, the William F. Meggers Award and the Adolph Lomb Medal (OSA).

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Published

2023-03-23

How to Cite

Amin, J., Almas Anjum, M., Sharif, M. ., Kadry, S., & González Crespo, R. (2023). Visual Geometry Group based on U-Shaped Model for Liver/Liver Tumor Segmentation. IEEE Latin America Transactions, 21(4), 557–564. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/7604

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