54 citations · 74 across the 6 of their papers we have counts for
6 papers
A novel inverse algorithm to solve IPO-IMPT of proton FLASH therapy with sparse filters
Nathan Harrison, Minglei Kang, Ruirui Liu +9
Purpose:The recently proposed IPO-IMPT framework allows simultaneous optimization of dose, dose rate, and LET for FLASH treatment planning. Finding solutions to IPO-IMPT is difficu…
Deep learning-based Fast Volumetric Image Generation for Image-guided Proton FLASH Radiotherapy
Chih-Wei Chang, Yang Lei, Tonghe Wang +7
Proton FLASH therapy leverages ultra-high dose-rate radiation to enhance the sparing of organs at risk without compromising tumor control probability. To prepare for the delivery o…
Deformable Image Registration using Unsupervised Deep Learning for CBCT-guided Abdominal Radiotherapy
Huiqiao Xie, Yang Lei, Yabo Fu +6
CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fraction…
An Integrated Biological Optimization framework for proton SBRT FLASH treatment planning allows dose, dose rate, and LET optimization using patient-specific ridge filters
Ruirui Liu, Serdar Charyyev, Niklas Wahl +10
Purpose: Patient-specific ridge filters can modulate proton energy to obtain a conformal dose. We describe a new framework for optimization of filter design and spot maps to meet t…
Knowledge-based Radiation Treatment Planning: A Data-driven Method Survey
Shadab Momin, Yabo Fu, Yang Lei +5
This paper surveys the data-driven dose prediction approaches introduced for knowledge-based planning (KBP) in the last decade. These methods were classified into two major categor…
Deep learning-based Real-time Volumetric Imaging for Lung Stereotactic Body Radiation Therapy: A Proof of Concept Study
Yang Lei, Zhen Tian, Tonghe Wang +5
Due to the inter- and intra- variation of respiratory motion, it is highly desired to provide real-time volumetric images during the treatment delivery of lung stereotactic body ra…