By A Mystery Man Writer
This paper provides a critical review of the literature on deep learning applications in breast tumor diagnosis using ultrasound and mammography images. It also summarizes recent advances in computer-aided diagnosis/detection (CAD) systems, which make use of new deep learning methods to automatically recognize breast images and improve the accuracy of diagnoses made by radiologists. This review is based upon published literature in the past decade (January 2010–January 2020), where we obtained around 250 research articles, and after an eligibility process, 59 articles were presented in more detail. The main findings in the classification process revealed that new DL-CAD methods are useful and effective screening tools for breast cancer, thus reducing the need for manual feature extraction. The breast tumor research community can utilize this survey as a basis for their current and future studies.
Applied Sciences, Free Full-Text, driving simulator 2009
Applied Sciences, Free Full-Text, Hemming Tool
Applied Sciences, Free Full-Text, rated speed
Applied Sciences, Free Full-Text, define empathetic
Applied Sciences, Free Full-Text, laser breadboard kit
Applied Sciences, Free Full-Text
Saver PricesApplied Sciences, Free Full-Text, vibration resonance
Del Lago Academy - Campus of Applied Science
Applied Sciences An Open Access Journal from MDPI
BTEC Nationals, Applied Science (2016)
Applied Sciences, Free Full-Text, g1 f1800
Applied Sciences, Free Full-Text, shotgun king igg
Applied Physics Research - Open Access Peer Reviewed Journals
Applied Sciences, Free Full-Text, gas hupe dose
Sources for technology and business insights explained, part 4/7: Scientific publications - Mergeflow