Recently, the diffusion model has emerged as a superior generative model...
Background and purpose: Radiation-induced erectile dysfunction (RiED) is...
When a pre-trained general auto-segmentation model is deployed at a new
...
In the past decade, deep learning (DL)-based artificial intelligence (AI...
Prediction uncertainty estimation has clinical significance as it can
po...
CBCT-based online adaptive radiotherapy (ART) calls for accurate
auto-se...
Medical image registration is a fundamental and vital task which will af...
Online adaptive radiotherapy (ART) requires accurate and efficient
auto-...
Automatic segmentation of anatomical structures is critical for many med...
Typically, the current dose prediction models are limited to small amoun...
In this study, we propose a tailored DL framework for patient-specific
p...
Since the outbreak of the COVID-19 pandemic, worldwide research efforts ...
Automatic segmentation of medical images with DL algorithms has proven t...
In tumor segmentation, inter-observer variation is acknowledged to be a
...
Low Dose Computed Tomography (LDCT) is clinically desirable due to the
r...
Monte Carlo (MC) simulation is considered the gold standard method for
r...
Low dose computed tomography (LDCT) is desirable for both diagnostic ima...
Recently, artificial intelligence technologies and algorithms have becom...
This work aims to study the generalizability of a pre-developed deep lea...
We propose to develop deep learning models that can predict Pareto optim...
Despite the indispensable role of X-ray computed tomography (CT) in
diag...
In post-operative radiotherapy for prostate cancer, the cancerous prosta...
Generalizability is a concern when applying a deep learning (DL) model
t...
Due to the large combinatorial problem, current beam orientation optimiz...
Automatically standardizing nomenclature for anatomical structures in
ra...
We propose a novel domain specific loss, which is a differentiable loss
...
An indoor, real-time location system (RTLS) can benefit both hospitals a...
The use of neural networks to directly predict three-dimensional dose
di...
To predict lung nodule malignancy with a high sensitivity and specificit...
Accurately classifying malignancy of lesions detected in a screening sca...
Accurate segmentation of prostate and surrounding organs at risk is impo...
The treatment planning process for patients with head and neck (H&N) can...
Data cleaning consumes about 80
clinical research projects. This is a mu...
With the advancement of treatment modalities in radiation therapy, outco...
Neural networks are known to be effective function approximators. Recent...