Analysis of algorithms for detecting breast cancer using medical imaging
Journal Title: Modern Innovations, Systems and Technologies - Year 2025, Vol 5, Issue 1
Abstract
This article is dedicated to modern methods of image detection and analysis. It discusses the SSD (Single Shot Multibox Detector) algorithm, which allows the detection of multiple objects in an image, as well as advanced approaches such as Vision Transformers (ViT) and Generative Adversarial Networks (GAN). The SSD method is designed for image analysis and precise object detection, while ViT divides an image into patches and focuses attention on each segment. GANs are used to generate new data that resembles real ones. The article also examines traditional and modern methods used in medical image analysis, including segmentation, filtering, and deep learning techniques. The use of machine learning algorithms, such as CNN, SVM, and others, achieves high accuracy in image analysis, while advanced methods like U-Net and YOLO are widely used in medicine for detecting organs or pathological changes. Additionally, the article explores the algorithms and methods employed in medical image analysis, including segmentation, object detection, and image restoration. Modern technologies and approaches, particularly Vision Transformer (ViT) and other cutting-edge architectures, provide high efficiency, making the analysis of medical images faster and more accurate.
Authors and Affiliations
Sh. N. Yo‘ldoshev, S. O. Otakhonova
Keywords
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- EP ID EP770138
- DOI 10.47813/2782-2818-2025-5-1-2046-2060
- Views 3
- Downloads 0
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