23 citations · 48 across the 8 of their papers we have counts for
8 papers
Artificial Intelligence-Enhanced Couinaud Segmentation for Precision Liver Cancer Therapy
Liang Qiu, Wenhao Chi, Xiaohan Xing +8
Precision therapy for liver cancer necessitates accurately delineating liver sub-regions to protect healthy tissue while targeting tumors, which is essential for reducing recurrenc…
Automated radiotherapy treatment planning guided by GPT-4Vision
Sheng Liu, Oscar Pastor-Serrano, Yizheng Chen +10
Objective: Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires the iterative adjustment of model parameters to balance multiple con…
A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy
Oscar Pastor-Serrano, Steven Habraken, Mischa Hoogeman +5
In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. Motion models can be used to simulate motion pattern…
Sub-second photon dose prediction via transformer neural networks
Oscar Pastor-Serrano, Peng Dong, Charles Huang +2
Fast dose calculation is critical for online and real time adaptive therapy workflows. While modern physics-based dose algorithms must compromise accuracy to achieve low computatio…
Learning Image Representations for Content Based Image Retrieval of Radiotherapy Treatment Plans
Charles Huang, Varun Vasudevan, Oscar Pastor-Serrano +7
Objective: Knowledge based planning (KBP) typically involves training an end-to-end deep learning model to predict dose distributions. However, training end-to-end methods may be a…
Millisecond speed deep learning based proton dose calculation with Monte Carlo accuracy
Oscar Pastor-Serrano, Zoltán Perkó
Next generation online and real-time adaptive radiotherapy workflows require precise particle transport simulations in sub-second times, which is unfeasible with current analytical…
Learning the Physics of Particle Transport via Transformers
Oscar Pastor-Serrano, Zoltán Perkó
Particle physics simulations are the cornerstone of nuclear engineering applications. Among them radiotherapy (RT) is crucial for society, with 50% of cancer patients receiving rad…
A semi-supervised autoencoder framework for joint generation and classification of breathing
Oscar Pastor-Serrano, Danny Lathouwers, Zoltán Perkó
One of the main problems with biomedical signals is the limited amount of patient-specific data and the significant amount of time needed to record the sufficient number of samples…