Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of cri...

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Detalles Bibliográficos
Autores principales: Aja-Fernández, Santiago, Martín-Martín, Carmen, Planchuelo-Gómez, Álvaro, Faiyaz, Abrar, Uddin, Md Nasir, Schifitto, Giovanni, Tiwari, Abhishek, Shigwan, Saurabh J., Kumar Singh, Rajeev, Zheng, Tianshu, Cao, Zuozhen, Wu, Dan, Blumberg, Stefano B., Sen, Snigdha, Goodwin-Allcock, Tobias, Slator, Paddy J., Yigit Avci, Mehmet, Li, Zihan, Bilgic, Berkin, Tian, Qiyuan, Wang, Xinyi, Tang, Zihao, Cabezas, Mariano, Rauland, Amelie, Merhof, Dorit, Manzano Maria, Renata, Campos, Vinícius Paraníba, Santini, Tales, da Costa Vieira, Marcelo Andrade, HashemizadehKolowri, SeyyedKazem, DiBella, Edward, Peng, Chenxu, Shen, Zhimin, Chen, Zan, Ullah, Irfan, Mani, Merry, Abdolmotalleby, Hesam, Eckstrom, Samuel, Baete, Steven H., Filipiak, Patryk, Dong, Tanxin, Fan, Qiuyun, de Luis-García, Rodrigo, Tristán-Vega, Antonio, Pieciak, Tomasz
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440596/
https://www.ncbi.nlm.nih.gov/pubmed/37572514
http://dx.doi.org/10.1016/j.nicl.2023.103483

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