AbstractThis synthetic dataset or phantom consists of 6 raw format databases, in the three–dimensional (3-D) domain, which are identified as follows:DB1: Ground TruthDB2: Poisson noiseDB3: Stair-step

DataCite Commons2022-06-10 更新50

Ground-truth simulation CT image in Figure 2 from Deep Learning-Based Artifact Reduction in Low-Dose Dental CBCT with High-Attenuation Materials

牙科CBCT成像

医学影像伪影

ref_200x200x30.raw

Figshare2025-08-04 更新10

Datasheet1_Modular GAN: positron emission tomography image reconstruction using two generative adversarial networks.docx

PET图像重建

医学图像伪影校正

IntroductionThe reconstruction of PET images involves converting sinograms, which represent the measured counts of radioactive emissions using detector rings encircling the patient, into meaningful im

NIAID Data Ecosystem00

Ground-truth simulation CT image in Figure 2 from Deep Learning-Based Artifact Reduction in Low-Dose Dental CBCT with High-Attenuation Materials

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