28 citations · 54 across the 8 of their papers we have counts for
8 papers
Sparse plus low-rank matrix embedding with applications in cancer radiotherapy optimization
Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh
Decomposing a matrix into sparse and low-rank components is central to robust principal component analysis and has broad applications in machine learning, signal processing, and co…
Automating RT Planning at Scale: High Quality Data For AI Training
Riqiang Gao, Mamadou Diallo, Han Liu +10
Radiotherapy (RT) planning is complex, subjective, and time-intensive. Advances with artificial intelligence (AI) promise to improve its precision and efficiency, but progress is o…
Compressed radiotherapy treatment planning (CompressRTP): A new paradigm for rapid and high-quality treatment planning optimization
Mojtaba Tefagh, Gourav Jhanwar, Masoud Zarepisheh
Background: Radiotherapy treatment planning involves solving large-scale optimization problems that are often approximated and solved sub-optimally due to time constraints. Central…
Distributed and Scalable Optimization for Robust Proton Treatment Planning
Anqi Fu, Vicki T. Taasti, Masoud Zarepisheh
Purpose: The importance of robust proton treatment planning to mitigate the impact of uncertainty is well understood. However, its computational cost grows with the number of uncer…
Simultaneous Reduction of Number of Spots and Energy Layers in Intensity Modulated Proton Therapy for Rapid Spot Scanning Delivery
Anqi Fu, Vicki T. Taasti, Masoud Zarepisheh
Reducing proton treatment time improves patient comfort and decreases the risk of error from intra-fractional motion, but must be balanced against clinical goals and treatment plan…
RMSim: Controlled Respiratory Motion Simulation on Static Patient Scans
Donghoon Lee, Ellen Yorke, Masoud Zarepisheh +2
This work aims to generate realistic anatomical deformations from static patient scans. Specifically, we present a method to generate these deformations/augmentations via deep lear…
Domain Knowledge Driven 3D Dose Prediction Using Moment-Based Loss Function
Gourav Jhanwar, Navdeep Dahiya, Parmida Ghahremani +2
Dose volume histogram (DVH) metrics are widely accepted evaluation criteria in the clinic. However, incorporating these metrics into deep learning dose prediction models is challen…
Deep Learning 3D Dose Prediction for Conventional Lung IMRT Using Consistent/Unbiased Automated Plans
Navdeep Dahiya, Gourav Jhanwar, Anthony Yezzi +2
Deep learning (DL) 3D dose prediction has recently gained a lot of attention. However, the variability of plan quality in the training dataset, generated manually by planners with…