Enhancing global sensitivity and uncertainty quantification in medical image reconstruction with Monte Carlo arbitrary-masked mamba

Deep learning has been extensively applied in medical image reconstruction, where Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) represent the predominant paradigms, each possessing distinct advantages and inherent limitations: CNNs exhibit linear complexity with local sensitivi...

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Veröffentlicht in:	Medical image analysis 2025-01, Vol.99, p.103334, Article 103334
Hauptverfasser:	Huang, Jiahao, Yang, Liutao, Wang, Fanwen, Wu, Yinzhe, Nan, Yang, Wu, Weiwen, Wang, Chengyan, Shi, Kuangyu, Aviles-Rivero, Angelica I., Schönlieb, Carola-Bibiane, Zhang, Daoqiang, Yang, Guang
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Deep Learning Humans Image Processing, Computer-Assisted - methods Mamba Medical image reconstruction Monte Carlo Method Neural Networks, Computer Sensitivity and Specificity Uncertainty Wavelet Wavelet Analysis
Online-Zugang:	Volltext
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