Gebruikersprofielen voor Ti Bai
Ti BaiUT Southwestern Medical Center Geverifieerd e-mailadres voor UTSouthwestern.edu Geciteerd door 638 |
A practical cone-beam CT scatter correction method with optimized Monte Carlo simulations for image-guided radiation therapy
Cone-beam CT (CBCT) has become the standard image guidance tool for patient setup in
image-guided radiation therapy. However, due to its large illumination field, scattered photons …
image-guided radiation therapy. However, due to its large illumination field, scattered photons …
Real-time liver tumor localization via a single x-ray projection using deep graph neural network-assisted biomechanical modeling
Objective. Real-time imaging is highly desirable in image-guided radiotherapy, as it provides
instantaneous knowledge of patients' anatomy and motion during treatments and enables …
instantaneous knowledge of patients' anatomy and motion during treatments and enables …
Towards the clinical implementation of iterative low‐dose cone‐beam CT reconstruction in image‐guided radiation therapy: Cone/ring artifact correction and multiple …
Purpose: Compressed sensing (CS)‐based iterative reconstruction (IR) techniques are able
to reconstruct cone‐beam CT (CBCT) images from undersampled noisy data, allowing for …
to reconstruct cone‐beam CT (CBCT) images from undersampled noisy data, allowing for …
Deep dose plugin: towards real-time Monte Carlo dose calculation through a deep learning-based denoising algorithm
Monte Carlo (MC) simulation is considered the gold standard method for radiotherapy dose
calculation. However, achieving high precision requires a large number of simulation …
calculation. However, achieving high precision requires a large number of simulation …
Probabilistic self‐learning framework for low‐dose CT denoising
Purpose Despite the indispensable role of x‐ray computed tomography (CT) in diagnostic
medicine, the associated harmful ionizing radiation dose is a major concern, as it may cause …
medicine, the associated harmful ionizing radiation dose is a major concern, as it may cause …
Z-index parameterization for volumetric CT image reconstruction via 3-D dictionary learning
Despite the rapid developments of X-ray cone-beam CT (CBCT), image noise still remains a
major issue for the low dose CBCT. To suppress the noise effectively while retain the …
major issue for the low dose CBCT. To suppress the noise effectively while retain the …
Improved segmentation of echocardiography with orientation-congruency of optical flow and motion-enhanced segmentation
Quantification of left ventricular (LV) ejection fraction (EF) from echocardiography depends
upon the identification of endocardium boundaries as well as the calculation of end-diastolic (…
upon the identification of endocardium boundaries as well as the calculation of end-diastolic (…
A feasibility study on deep learning‐based individualized 3D dose distribution prediction
Purpose Radiation therapy treatment planning is a trial‐and‐error, often time‐consuming
process. An approximately optimal dose distribution corresponding to a specific patient's …
process. An approximately optimal dose distribution corresponding to a specific patient's …
Synthesizing CT images from MR images with deep learning: model generalization for different datasets through transfer learning
Background and purpose. Replacing CT imaging with MR imaging for MR-only radiotherapy
has sparked the interest of many scientists and is being increasingly adopted in radiation …
has sparked the interest of many scientists and is being increasingly adopted in radiation …
Bony structure enhanced synthetic CT generation using Dixon sequences for pelvis MR‐only radiotherapy
Background MRI‐only radiotherapy planning (MROP) is beneficial to patients by avoiding
MRI/CT registration errors, simplifying the radiation treatment simulation workflow and …
MRI/CT registration errors, simplifying the radiation treatment simulation workflow and …