2D medical image synthesis using transformer-based denoising diffusion probabilistic model
Objective. Artificial intelligence (AI) methods have gained popularity in medical imaging
research. The size and scope of the training image datasets needed for successful AI model …
research. The size and scope of the training image datasets needed for successful AI model …
Synthetic CT generation from MRI using 3D transformer‐based denoising diffusion model
Background and purpose Magnetic resonance imaging (MRI)‐based synthetic computed
tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for …
tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for …
High-resolution MRI synthesis using a data-driven framework with denoising diffusion probabilistic modeling
Objective. High-resolution magnetic resonance imaging (MRI) can enhance lesion
diagnosis, prognosis, and delineation. However, gradient power and hardware limitations …
diagnosis, prognosis, and delineation. However, gradient power and hardware limitations …
Deep learning-based synthetic dose-weighted LET map generation for intensity modulated proton therapy
The advantage of proton therapy as compared to photon therapy stems from the Bragg peak
effect, which allows protons to deposit most of their energy directly at the tumor while sparing …
effect, which allows protons to deposit most of their energy directly at the tumor while sparing …
Validation of a deep learning-based material estimation model for Monte Carlo dose calculation in proton therapy
Objective. Computed tomography (CT) to material property conversion dominates proton
range uncertainty, impacting the quality of proton treatment planning. Physics-based and …
range uncertainty, impacting the quality of proton treatment planning. Physics-based and …
Single energy CT-based mass density and relative stopping power estimation for proton therapy using deep learning method
Background The number of patients undergoing proton therapy has increased in recent
years. Current treatment planning systems (TPS) calculate dose maps using three …
years. Current treatment planning systems (TPS) calculate dose maps using three …
MRI-only based material mass density and relative stopping power estimation via deep learning for proton therapy: a preliminary study
Abstract Magnetic Resonance Imaging (MRI) is increasingly being used in treatment
planning due to its superior soft tissue contrast, which is useful for tumor and soft tissue …
planning due to its superior soft tissue contrast, which is useful for tumor and soft tissue …
Multimodal imaging-based material mass density estimation for proton therapy using supervised deep learning
Objective Mapping CT number to material property dominates the proton range uncertainty.
This work aims to develop a physics-constrained deep learning-based multimodal imaging …
This work aims to develop a physics-constrained deep learning-based multimodal imaging …
Robust explanation supervision for false positive reduction in pulmonary nodule detection
Background Lung cancer is the deadliest and second most common cancer in the United
States due to the lack of symptoms for early diagnosis. Pulmonary nodules are small …
States due to the lack of symptoms for early diagnosis. Pulmonary nodules are small …
[HTML][HTML] Data-Driven Volumetric Image Generation from Surface Structures using a Patient-Specific Deep Leaning Model
The advent of computed tomography significantly improves patients' health regarding
diagnosis, prognosis, and treatment planning and verification. However, tomographic …
diagnosis, prognosis, and treatment planning and verification. However, tomographic …