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Sundar, L.K.S., Yu, J., Muzik, O., Kulterer, O.C., Fueger, B., Kifjak, D., et al. (2022) Fully Automated, Semantic Segmentation of Whole-Body ¹⁸F-FDG PET/CT Images Based on Data-Centric Artificial Intelligence. Journal of Nuclear Medicine, 63, 1941-1948.
https://doi.org/10.2967/jnumed.122.264063

has been cited by the following article:

• TITLE: Advances in Total-Body PET/CT Research

  AUTHORS: Chushan Yan, Jiehua Xu

  KEYWORDS: Whole Body Imaging, Positron-Emission Tomography, Tomography, X-Ray Computer

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.14 No.1, January 19, 2026

  ABSTRACT: With the iterative advancement of PET/CT technology, uEXPLORER, the first ultra-long axial field-of-view (LAFOV) PET/CT system enabling single-bed-position whole-body imaging has entered clinical use. This scanner significantly enhances molecular imaging performance through ultra-fast scanning, low-dose imaging, whole-body dynamic imaging, and simultaneous multi-tracer imaging capabilities. Recently, we have witnessed rapid growth in related research, which primarily focused on single imaging protocol optimization and clinical application exploration. This article systematically reviews current studies on uEXPLORER, aiming to inform future research directions.