Deep supervised transformer-based noise-aware network for low-dose PET denoising across varying count levels.
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| Title: | Deep supervised transformer-based noise-aware network for low-dose PET denoising across varying count levels. |
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| Authors: | Azimi MS; Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran., Felfelian V; Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran, Iran., Zeraatkar N; Department of Radiology, University of Massachusetts Chan Medical School, 55 Lake Avenue North, Worcester, MA, USA., Dadgar H; Imam Reza Cancer Research Center, Nuclear Medicine and Molecular Imaging Department, RAZAVI Hospital, Mashhad, Iran., Arabi H; Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland., Zaidi H; Division of Nuclear Medicine & Molecular Imaging, Geneva University Hospital, CH-1211, Geneva, Switzerland; Department of Nuclear Medicine and Molecular Imaging, University of Groningen, Groningen, Netherlands; Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark; University Research and Innovation Center, Óbuda University, Budapest, Hungary. Electronic address: habib.zaidi@hcuge.ch. |
| Source: | Computers in biology and medicine [Comput Biol Med] 2025 Sep; Vol. 196 (Pt A), pp. 110733. Date of Electronic Publication: 2025 Jul 08. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier Country of Publication: United States NLM ID: 1250250 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-0534 (Electronic) Linking ISSN: 00104825 NLM ISO Abbreviation: Comput Biol Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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