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Several robotic frameworks have been recently developed to assist ophthalmic surgeons in performing complex vitreoretinal procedures such as subretinal injection of advanced therapeutics. These surgical robots show promising capabilities;…
Purpose: This paper presents the preliminary results of a semi-automatic method for prostate segmentation of Magnetic Resonance Images (MRI) which aims to be incorporated in a navigation system for prostate brachytherapy. Methods: The…
Purpose: Radiotherapy commonly relies on CT, but there is growing interest in using hybrid PET/MR. Therefore, dedicated hardware setups have been proposed for PET/MR systems which enable imaging in radiotherapy treatment position. These…
Treatment planning uncertainties are typically managed using margin-based or robust optimization. Margin-based methods expand the clinical target volume (CTV) to a planning target volume, generally unsuited for proton therapy. Robust…
Purpose: The FLASH effect, which reduces the radiosensitivity of healthy tissue while maintaining tumor control at high dose rates, has shown potential for improving radiation therapy. Conformal FLASH proton therapy involves advanced…
In recent years, random subspace methods have been actively studied for large-dimensional nonconvex problems. Recent subspace methods have improved theoretical guarantees such as iteration complexity and local convergence rate while…
Lookahead, also known as non-myopic, Bayesian optimization (BO) aims to find optimal sampling policies through solving a dynamic program (DP) that maximizes a long-term reward over a rolling horizon. Though promising, lookahead BO faces the…
Radiology report generation requires advanced medical image analysis, effective temporal reasoning, and accurate text generation. Although recent innovations, particularly multimodal large language models, have shown improved performance,…
Radiation therapy is the primary method used to treat cancer in the clinic. Its goal is to deliver a precise dose to the planning target volume (PTV) while protecting the surrounding organs at risk (OARs). However, the traditional workflow…
We consider an optimization deployment problem of multistatic radar system (MSRS). Through the antenna placing and the transmitted power allocating, we optimally deploy the MSRS for two goals: 1) the first one is to improve the coverage…
We propose an oAPT workflow that incorporates all these functionalities and validate its clinical implementation feasibility with prostate patients. AI-based auto-segmentation tool AccuContourTM (Manteia, Xiamen, China) was seamlessly…
The purpose of this study is to give an exact formulation of optimization of volumetric-modulated arc therapy (VMAT) with sliding-window delivery, and to investigate the plan quality effects of decreasing the number of sliding-window sweeps…
High-dose-rate (HDR) brachytherapy plays a critical role in the treatment of locally advanced cervical cancer but remains highly dependent on manual treatment planning expertise. The objective of this study is to develop a fully automated…
Introduction: Intra-organ radiation dose sensitivity is becoming increasingly relevant in clinical radiotherapy. One method for assessment involves partitioning delineated regions of interest and comparing the relative contributions or…
Purpose: To develop a multi-criteria optimization framework for image guided radiotherapy. Methods: An algorithm is proposed for a multi-criteria framework for the purpose of patient setup verification decision processes. Optimal patient…
A central problem in the field of radiation therapy (RT) is how to optimally deliver dose to a patient in a way that fully accounts for anatomical position changes over time. As current RT is a static process, where beam intensities are…
Purpose: This study aims to optimize and characterize the response of a mPSD for in vivo dosimetry in HDR brachytherapy. Methods: An exhaustive analysis was carried out in order to obtain an optimized mPSD design that maximize the…
Non-geostationary (NGSO) satellite communications systems have attracted a lot of attention both from industry and academia, over the past several years. Beam placement is among the major resource allocation problems in multi-beam NGSO…
Radiotherapy treatment planning is a challenging large-scale optimization problem plagued by uncertainty. Following the robust optimization methodology, we propose a novel, spatially based uncertainty set for robust modeling of radiotherapy…
We propose to develop deep learning models that can predict Pareto optimal dose distributions by using any given set of beam angles, along with patient anatomy, as input to train the deep neural networks. We implement and compare two deep…