Linear diffusion noise boosted deep image prior for unsupervised sparse-view CT reconstruction

Deep learning has markedly enhanced the performance of sparse-view computed tomography reconstruction. However, the dependence of these methods on supervised training using high-quality paired datasets, and the necessity for retraining under varied physical acquisition conditions, constrain their ge...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Physics in medicine & biology 2024-08, Vol.69 (16), p.165029
Hauptverfasser:	Wu, Jia, Jiang, Xiaoming, Zhong, Lisha, Zheng, Wei, Li, Xinwei, Lin, Jinzhao, Li, Zhangyong
Format:	Artikel
Sprache:	eng
Schlagworte:	deep image prior (DIP) Deep Learning Diffusion diffusion noise Humans Image Processing, Computer-Assisted - methods multi-head attention Signal-To-Noise Ratio sparse-view Tomography, X-Ray Computed unsupervised CT reconstruction Unsupervised Machine Learning
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!