10 citations · 12 across the 3 of their papers we have counts for
3 papers
cs.CV2025★ 1 cited
PET Head Motion Estimation Using Supervised Deep Learning with Attention
Zhuotong Cai, Tianyi Zeng, Jiazhen Zhang +8
Head movement poses a significant challenge in brain positron emission tomography (PET) imaging, resulting in image artifacts and tracer uptake quantification inaccuracies. Effecti…
eess.IV2023★ 1 cited
Fast-MC-PET: A Novel Deep Learning-aided Motion Correction and Reconstruction Framework for Accelerated PET
Bo Zhou, Yu-Jung Tsai, Jiazhen Zhang +7
Patient motion during PET is inevitable. Its long acquisition time not only increases the motion and the associated artifacts but also the patient's discomfort, thus PET accelerati…
eess.IV2019★ 10 cited
A Novel Loss Function Incorporating Imaging Acquisition Physics for PET Attenuation Map Generation using Deep Learning
Luyao Shi, John A. Onofrey, Enette Mae Revilla +6
In PET/CT imaging, CT is used for PET attenuation correction (AC). Mismatch between CT and PET due to patient body motion results in AC artifacts. In addition, artifact caused by m…