This chapter provides an introductory summary of recent advancements in deep learning and its role in modern computer-aided diagnosis and treatment systems. The chapter elaborates on particular deep learning architectures, like convolutional neural networks and generative adversarial networks, and provides a minimum technical background before analyzing their applications in the field. In the second half, the chapter focuses on recent developments of medical deep learning applications in the specific field of maxillofacial imaging with a focus also on perceptual loss functions and uncertainty-aware deep learning.
Deep learning and generative adversarial networks in oral and maxillofacial surgery / Pepe, Antonio; Trotta, Gianpaolo Francesco; Gsaxner, Christina; Brunetti, Antonio; Cascarano, Giacomo Donato; Bevilacqua, Vitoantonio; Shen, Dinggang; Egger, Jan - In: Computer-Aided Oral and Maxillofacial Surgery : Developments, Applications, and Future Perspectives / [a cura di] Jan Egger, Xiaojun Chen. - STAMPA. - [s.l] : Elsevier - Academic Press, 2021. - ISBN 978-0-12-823299-6. - pp. 55-82 [10.1016/B978-0-12-823299-6.00003-1]
Deep learning and generative adversarial networks in oral and maxillofacial surgery
Trotta, Gianpaolo Francesco;Brunetti, Antonio;Cascarano, Giacomo Donato;Bevilacqua, Vitoantonio;
2021-01-01
Abstract
This chapter provides an introductory summary of recent advancements in deep learning and its role in modern computer-aided diagnosis and treatment systems. The chapter elaborates on particular deep learning architectures, like convolutional neural networks and generative adversarial networks, and provides a minimum technical background before analyzing their applications in the field. In the second half, the chapter focuses on recent developments of medical deep learning applications in the specific field of maxillofacial imaging with a focus also on perceptual loss functions and uncertainty-aware deep learning.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.