activity
20202024
most citedCharacterization of a novel time-resolved, real-time scintillation dosimetry system for ultra-high dose rate radiation therapy applications

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

physics.med-ph2024★ 3 cited

Characterization of a novel time-resolved, real-time scintillation dosimetry system for ultra-high dose rate radiation therapy applications

Alexander Baikalov, Daline Tho, Kevin Liu +3

Background: Scintillation dosimetry has promising qualities for ultra-high dose rate (UHDR) radiotherapy (RT), but no system has shown compatibility with mean dose rates ($\bar{DR}…

physics.med-ph2022

Differential tissue sparing of FLASH ultra high dose rates: an {\it in-silico} study

Ramin Abolfath, Alexander Baikalov, Sohrab Rahvar +4

Purpose: To propose a theory for the differential tissue sparing of FLASH ultra high dose rates (UHDR) through inter-track reaction-diffusion mechanism. Methods: We calculate the t…

physics.med-ph2022★ 3 cited

Modeling interspur interactions as a potential mechanism of the FLASH effect

Alexander Baikalov, Ramin Abolfath, Radhe Mohan +3

The mechanism responsible for the FLASH effect, normal tissue sparing by ultra-high dose rate (UHDR) irradiation with isoeffective tumor control compared to conventional dose rate…

physics.med-ph2022

The effect of non-ionizing excitations on the diffusion of ion species and inter-track correlations in FLASH ultra-high dose rate radiotherapy

Ramin Abolfath, Alexander Baikalov, Stefan Bartzsch +2

We present a microscopic mechanism that accounts for the outward burst of "cold" ion species (IS) in a high-energy particle track due to coupling with ''hot" non-ion species (NIS).…

eess.IV2020

Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients

Daniel M. Lang, Jan C. Peeken, Stephanie E. Combs +2

We investigated the ability of deep learning models for imaging based HPV status detection. To overcome the problem of small medical datasets we used a transfer learning approach.…