This paper reviewed the deep learning‐based studies for medical imaging synthesis and its
clinical application. Specifically, we summarized the recent developments of deep learning …

While proton radiation therapy offers substantially better dose distribution characteristics
than photon radiation therapy in certain clinical applications, data demonstrating a …

In x‐ray computed tomography (CT), materials with different elemental compositions can
have identical CT number values, depending on the mass density of each material and the …

Purpose To quantifiy the range uncertainty in proton treatment planning using dual-energy
computed tomography (DECT) for a direct stopping-power prediction (DirectSPR) algorithm …

Pre-treatment CT imaging is a topic of growing importance in particle therapy. Improvements
in the accuracy of stopping-power prediction are demanded to allow for a dose conformality …

Accurate determination of physical/mass and electron densities are critical to accurate
spatial and dosimetric delivery of radiotherapy for photon and charged particles. In this …

Range uncertainty has been a key factor preventing particle radiotherapy from reaching its
full physical potential. One of the main contributing sources is the uncertainty in estimating …

Over the past decade, spectral or dual‐energy CT has gained relevancy, especially in
oncological radiology. Nonetheless, its use in the radiotherapy (RT) clinic remains limited …

Background and purpose To reduce range uncertainty in particle therapy, an accurate
computation of stopping-power ratios (SPRs) based on computed tomography (CT) is …

Background and purpose Stopping-power ratios (SPRs) are used in particle therapy to
calculate particle range in patients. The heuristic CT-to-SPR conversion (Hounsfield Look …