28 citations · 32 across the 4 of their papers we have counts for
4 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…
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…
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…