Investigating focal spot position drift in a mobile imaging system equipped with a monobloc-based x-ray generator.

Background: Misalignment or double-contouring artifacts can appear in high-resolution 3D cone beam computed tomography (CBCT) images, potentially indicating geometric accuracy issues in the projection data. Such artifacts may go unnoticed in low-resolution images and could be associated with changes in the focal spot (FS) position.

Purpose: High-resolution 3D-CBCT imaging by a mobile imaging device with a large gantry clearance offers more versatility for clinical workflows in image-guided brachytherapy (IGBT), intraoperative radiation therapy (IORT), and spinal, as well as maxillofacial surgery.

A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder.

The primary cone-beam computed tomography (CBCT) imaging beam scatters inside the patient and produces a contaminating photon fluence that is registered by the detector. Scattered photons cause artifacts in the image reconstruction, and are partially responsible for the inferior image quality compared to diagnostic fan-beam CT. In this work, a deep convolutional autoencoder (DCAE) and projection-based scatter removal algorithm were constructed for the ImagingRing system on rails (IRr), which allows for non-isocentric acquisitions around virtual rotation centers with its independently rotatable source and detector arms.

Modelling of the focal spot intensity distribution and the off-focal spot radiation in kilovoltage x-ray tubes for imaging.

X-ray tubes for medical applications typically generate x-rays by accelerating electrons, emitted from a cathode, with an interelectrode electric field, towards an anode target. X-rays are not emitted from one point, but from an irregularly shaped area on the anode, the focal spot. Focal spot intensity distributions and off-focal radiation negatively affect the imaging spatial resolution and broadens the beam penumbra.