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Gray-to-color image conversion in the classification of breast lesions on ultrasound using pre-trained deep neural networks., и . Medical Biol. Eng. Comput., 61 (12): 3193-3207 (декабря 2023)Evaluating the performance of convolutional neural networks with direct acyclic graph architectures in automatic segmentation of breast lesion in US images., , , , и . BMC Medical Imaging, 19 (1): 85:1-85:13 (2019)Breast Lesion Classification in Ultrasound Images Using Deep Convolutional Neural Network., , , , , и . IEEE Access, (2020)Breast tumor classification in ultrasound images using neural networks with improved generalization methods., , , и . EMBC, стр. 6321-6325. IEEE, (2015)Ultrasonic Attenuation and Speed in phantoms made of PVCP and Evaluation of acoustic and thermal properties of ultrasonic phantoms made of polyvinyl chloride-plastisol (PVCP)., , , , и . IWBBIO, стр. 233-241. Copicentro Editorial, (2013)A contrast enhancement method for improving the segmentation of breast lesions on ultrasonography., и . Comput. Biol. Medicine, (2017)BUSAT: A MATLAB Toolbox for Breast Ultrasound Image Analysis., , и . MCPR, том 10267 из Lecture Notes in Computer Science, стр. 268-277. Springer, (2017)Applying a novelty filter as a matching criterion to iris recognition for binary and real-valued feature vectors., , , и . Signal Image Video Process., 7 (2): 287-296 (2013)A comparative study of pre-trained convolutional neural networks for semantic segmentation of breast tumors in ultrasound., и . Comput. Biol. Medicine, (2020)A computer-aided diagnosis system for breast ultrasound based on weighted BI-RADS classes., , и . Comput. Methods Programs Biomed., (2018)