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:: Volume 4, Issue 8 (9-2025) ::
3 2025, 4(8): 0-0 Back to browse issues page
Deep Symmetry Applications in the Segmentation of Images in Medical Healthcare
Zahra Amiri , Arash Heidari , Nima Jafari Navimipour , Mansour Esmaeilpour
Ivy College of Business, Iowa State University, USA
Abstract:   (7 Views)
In the domain of deep symmetry applications in the segmentation of medical images, the utilization of state-of-the-art Deep Learning (DL) methodologies assumes paramount significance. Machine Learning (ML) has attained remarkable achievements across diverse domains, rendering its efficacy particularly noteworthy in the context of image segmentation within medical healthcare. The integration of DL with image segmentation enables real-time analysis of vast and intricate datasets, yielding insights that significantly enhance healthcare outcomes and operational efficiency in the industry. This comprehensive literature review systematically investigates the latest DL solutions for the challenges encountered in medical healthcare, with a specific emphasis on deep symmetry applications in image segmentation. By categorizing cutting-edge DL approaches into distinct categories, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Long Short-term Memory (LSTM) models, and hybrid models, this study delves into their underlying principles, merits, limitations, methodologies, simulation environments, and datasets. Notably, the majority of the scrutinized papers were published in 2021, underscoring the contemporaneous nature of the research. Moreover, this review accentuates the forefront advancements in DL techniques and their practical applications within the realm of image segmentation, while simultaneously addressing the challenges that hinder the widespread implementation of DL in image segmentation within the medical healthcare domains. These discerned insights serve as compelling impetuses for future studies aimed at the progressive advancement of image segmentation in medical healthcare research. The evaluation metrics employed across the reviewed articles encompass a broad spectrum of features, encompassing accuracy, sensitivity, specificity, F-score, latency, adaptability, and scalability.
Keywords: Machine Learning, Deep Learning, Image segmentation, Healthcare, medical image
Full-Text [PDF 1934 kb]   (11 Downloads)    
Type of Study: Research | Subject: Special
Received: 2025/09/16 | Accepted: 2025/05/31 | Published: 2025/05/31
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Amiri Z, Heidari A, Jafari Navimipour N, Esmaeilpour M. Deep Symmetry Applications in the Segmentation of Images in Medical Healthcare. 3 2025; 4 (8)
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Volume 4, Issue 8 (9-2025) Back to browse issues page
فصلنامه سیستم های اطلاعاتی هوشمند Intelligent Information Systems Journal
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