Design of Metaheuristic Optimization-Based Vascular Segmentation Techniques for Photoacoustic Images

Author:

Vaiyapuri Thavavel1ORCID,Dutta Ashit Kumar2ORCID,Sikkandar Mohamed Yacin3ORCID,Gupta Deepak4ORCID,Alouffi Bader5ORCID,Alharbi Abdullah6,Rauf Hafiz Tayyab7ORCID,Kadry Seifedine8ORCID

Affiliation:

1. College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia

2. Department of Computer Science and Information Systems, College of Applied Sciences, AlMaarefa University, Ad Diriyah, Riyadh 13713, Saudi Arabia

3. Department of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majmaah 11952, Saudi Arabia

4. Department of Computer Science & Engineering, Maharaja Agrasen Institute of Technology, Delhi, India

5. Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia

6. Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia

7. Department of Computer Science, Faculty of Engineering & Informatics, University of Bradford, Bradford, UK

8. Faculty of Applied Computing and Technology, Noroff University College, Kristiansand, Norway

Abstract

Biomedical imaging technologies are designed to offer functional, anatomical, and molecular details related to the internal organs. Photoacoustic imaging (PAI) is becoming familiar among researchers and industrialists. The PAI is found useful in several applications of brain and cancer imaging such as prostate cancer, breast cancer, and ovarian cancer. At the same time, the vessel images hold important medical details which offer strategies for a qualified diagnosis. Recently developed image processing techniques can be employed to segment vessels. Since vessel segmentation on PAI is a difficult process, this paper employs metaheuristic optimization-based vascular segmentation techniques for PAI. The proposed model involves two distinct kinds of vessel segmentation approaches such as Shannon’s entropy function (SEF) and multilevel Otsu thresholding (MLOT). Moreover, the threshold value and entropy function in the segmentation process are optimized using three metaheuristics such as the cuckoo search (CS), equilibrium optimizer (EO), and harmony search (HS) algorithms. A detailed experimental analysis is made on benchmark PAI dataset, and the results are inspected under varying aspects. The obtained results pointed out the supremacy of the presented model with a higher accuracy of 98.71%.

Funder

Taif University

Publisher

Hindawi Limited

Subject

Radiology, Nuclear Medicine and imaging

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