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Damian Valdés-Santiago, Angela M. León-Mecías, Marta Lourdes Baguer Díaz-Romañach, Antoni Jaume-i-Capó, Manuel González-Hidalgo and Jose Maria Buades Rubio
This contribution presents a wavelet-based algorithm to detect patterns in images. A two-dimensional extension of the DST-II is introduced to construct adapted wavelets using the equation of the tensor product corresponding to the diagonal coefficients i...
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Fahimeh Aminolroayaei, Saghar Shahbazi-Gahrouei, Amir Khorasani and Daryoush Shahbazi-Gahrouei
Breast cancer is the foremost common cause of death in women, and its early diagnosis will help treat and increase patients? survival. This review article aims to look at the studies on the recent findings of standard imaging techniques and their charact...
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Zahra Jafari and Ebrahim Karami
The prompt and accurate diagnosis of breast lesions, including the distinction between cancer, non-cancer, and suspicious cancer, plays a crucial role in the prognosis of breast cancer. In this paper, we introduce a novel method based on feature extracti...
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Miu Sakaida, Takaaki Yoshimura, Minghui Tang, Shota Ichikawa and Hiroyuki Sugimori
Convolutional neural networks (CNNs) in deep learning have input pixel limitations, which leads to lost information regarding microcalcification when mammography images are compressed. Segmenting images into patches retains the original resolution when i...
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Rowa Aljondi, Salem Saeed Alghamdi, Abdulrahman Tajaldeen, Shareefah Alassiri, Monagi H. Alkinani and Thomas Bertinotti
Background: Breast cancer has a 14.8% incidence rate and an 8.5% fatality rate in Saudi Arabia. Mammography is useful for the early detection of breast cancer. Researchers have been developing artificial intelligence (AI) algorithms for early breast canc...
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Mohammad H. Alshayeji and Jassim Al-Buloushi
Improved disease prediction accuracy and reliability are the main concerns in the development of models for the medical field. This study examined methods for increasing classification accuracy and proposed a precise and reliable framework for categorizi...
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Jöran Rixen, Nico Blass, Simon Lyra and Steffen Leonhardt
Breast cancer is the leading cause of cancer-related death among women. Early prediction is crucial as it severely increases the survival rate. Although classical X-ray mammography is an established technique for screening, many eligible women do not con...
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N. Aidossov, Vasilios Zarikas, Aigerim Mashekova, Yong Zhao, Eddie Yin Kwee Ng, Anna Midlenko and Olzhas Mukhmetov
Breast cancer comprises a serious public health concern. The three primary techniques for detecting breast cancer are ultrasound, mammography, and magnetic resonance imaging (MRI). However, the existing methods of diagnosis are not practical for regular ...
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Nada Fitrieyatul Hikmah, Tri Arief Sardjono, Windy Deftia Mertiana, Nabila Puspita Firdi, Diana Purwitasari
Pág. 136 - 152
Breast cancer is the leading cause of cancer death in women. The early phase of breast cancer is asymptomatic, without any signs or symptoms. The earlier breast cancer can be detected, the greater chance of cure. Early detection using screening mammograp...
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Pi-Yun Chen, Xuan-Hao Zhang, Jian-Xing Wu, Ching-Chou Pai, Jin-Chyr Hsu, Chia-Hung Lin and Neng-Sheng Pai
Mammography is a first-line imaging examination approach used for early breast tumor screening. Computational techniques based on deep-learning methods, such as convolutional neural network (CNN), are routinely used as classifiers for rapid automatic bre...
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