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The Utility of Deep Learning in Breast Ultrasonic Imaging: A Review

Breast cancer is the most frequently diagnosed cancer in women; it poses a serious threat to women’s health. Thus, early detection and proper treatment can improve patient prognosis. Breast ultrasound is one of the most commonly used modalities for diagnosing and detecting breast cancer in clinical...

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Detalles Bibliográficos
Autores principales: Fujioka, Tomoyuki, Mori, Mio, Kubota, Kazunori, Oyama, Jun, Yamaga, Emi, Yashima, Yuka, Katsuta, Leona, Nomura, Kyoko, Nara, Miyako, Oda, Goshi, Nakagawa, Tsuyoshi, Kitazume, Yoshio, Tateishi, Ukihide
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7762151/
https://www.ncbi.nlm.nih.gov/pubmed/33291266
http://dx.doi.org/10.3390/diagnostics10121055
Descripción
Sumario:Breast cancer is the most frequently diagnosed cancer in women; it poses a serious threat to women’s health. Thus, early detection and proper treatment can improve patient prognosis. Breast ultrasound is one of the most commonly used modalities for diagnosing and detecting breast cancer in clinical practice. Deep learning technology has made significant progress in data extraction and analysis for medical images in recent years. Therefore, the use of deep learning for breast ultrasonic imaging in clinical practice is extremely important, as it saves time, reduces radiologist fatigue, and compensates for a lack of experience and skills in some cases. This review article discusses the basic technical knowledge and algorithms of deep learning for breast ultrasound and the application of deep learning technology in image classification, object detection, segmentation, and image synthesis. Finally, we discuss the current issues and future perspectives of deep learning technology in breast ultrasound.