For the 24 scans acquired with hardware-based gating, the gating signal was acquired using a Biovet® gating system (Biovet®, M2Mimaging, Cleveland, OH, USA).
Twenty four of the scans (11 18F-FDG, 5 11C-DMDPA, 4 18F-FEDPMA, and 4 18F-FBDPMA) were acquired with hardware-based respiratory gating, and for this subset of scans, hardware-based signals were compared with the corresponding software-based signal.
Only one patient with small number of metal dental hardware was acquired with a jaw spacer installed, showing a reduction of artifact volume by 49.3% when reconstructed with the dedicated iterative metal artifact reduction algorithm (3.4 ± 6.7 ml).
To circumvent this problem, it is proposed a new automated image-processing algorithm that identifies sand grains in digital images acquired with a standard digital camera without any extra hardware attached to it.
The proposed method is investigated for non-TOF PET phantom and 18F-FDG patient data acquired with a clinical PET/MR device, using headphones or RF surface coils as flexible hardware components.
For example, the TTV method does not require hardware modifications to the OCT system and can be applied to images acquired with any commercially available or research grade OCT technology.
Moreover, we evaluated MLAA-based hardware attenuation estimation for pneumatic headphones and for a six-channel torso RF surface coil using both phantom and patient non-TOF PET data acquired with a Siemens Biograph mMR (Siemens Healthineers, Erlangen, Germany).
And data were acquired with FACSAria.
Images were acquired with an Olympus BX41.
Images were acquired with the LSM510 software.
