Deep Learning Methods in the Problem of Breast Cancer Detection
DOI:
https://doi.org/10.52575/2687-0932-2025-52-4-861-872Keywords:
neural networks, ultrasound, elastography, pairwise loss functions, machine learningAbstract
Deep learning methods and algorithms are currently being actively used in the medical field. One of the tasks in which neural networks achieve good results is diagnostics. The use of systems incorporating deep learning algorithms for diagnostic studies is particularly beneficial in situations where there is a shortage of medical personnel, particularly highly qualified specialists. This article examines current research in the field of breast cancer recognition from ultrasound images, the most common method due to its non-invasive nature. The analysis includes studies from the past five years in this field. The paper also presents the authors' considerations for developing a new deep learning algorithm for breast cancer recognition from ultrasound images, based on the use of a pair of loss functions in network construction. Advances in ultrasound technology have made it possible to obtain higher-quality and more informative images, improving the accuracy of malignant tumor diagnosis using deep learning techniques.
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