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2000
Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Introduction

This study intends to provide a novel Invasive Weed Optimization (IWO) algorithm for the detection of Polycystic Ovary Syndrome (PCOS) from ultrasound ovarian images. PCOS is an intricate anarchy described by hyperandrogenemia and irregular menstruation. Indian women are increasingly finding reproductive disorders, namely PCOS.

Methods

The women having PCOS grow more small follicles in their ovaries. The radiologists take a look into women's ovaries by use of ultrasound scanning equipment to manually count the number of follicles and their size for fertility treatment. These may lead to error diagnosis.

Results

This paper proposed an automatic follicle detection system for identifying PCOS in the ovary using IWO. The performance of IWO is improved in Modified Invasive Weed Optimization (MIWO). This algorithm imitates the biological weeds' behavior. The MIWO is employed to obtain the optimal threshold by maximizing the between-class variance of the modified Otsu method. The efficiency of the proposed method has been compared with the well-known optimization technique called Particle Swarm Optimization (PSO) and with IWO.

Conclusion

Experimental results proved that the MIWO finds an optimal threshold higher than that of IWO and PSO.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2024-01-01
2025-08-19

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/content/journals/cmir/10.2174/0115734056307615240823074030
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A Novel Invasive Weed Optimization and its Variant for the Detection of Polycystic Ovary Syndrome
Curr. Med. Imaging 20, e15734056307615 (2024); https://doi.org/10.2174/0115734056307615240823074030
/content/journals/cmir/10.2174/0115734056307615240823074030
/content/journals/cmir/10.2174/0115734056307615240823074030
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  • Article Type:     Research Article
Keyword(s): Follicles; Invasive weed optimization; Modified Invasive Weed Optimization; Modified Otsu; Particle swarm optimization; Polycystic ovaries

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