
Deep Dose Plugin Towards Realtime Monte Carlo Dose Calculation Through a Deep Learning based Denoising Algorithm
Monte Carlo (MC) simulation is considered the gold standard method for r...
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Deep Interactive Denoiser (DID) for XRay Computed Tomography
Low dose computed tomography (LDCT) is desirable for both diagnostic ima...
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Using Monte Carlo dropout and bootstrap aggregation for uncertainty estimation in radiation therapy dose prediction with deep learning neural networks
Recently, artificial intelligence technologies and algorithms have becom...
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Dose Prediction with Deep Learning for Prostate Cancer Radiation Therapy: Model Adaptation to Different Treatment Planning Practices
This work aims to study the generalizability of a predeveloped deep lea...
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Using Deep Learning to Predict BeamTunable Pareto Optimal Dose Distribution for Intensity Modulated Radiation Therapy
We propose to develop deep learning models that can predict Pareto optim...
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Probabilistic selflearning framework for Lowdose CT Denoising
Despite the indispensable role of Xray computed tomography (CT) in diag...
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A deep learningbased framework for segmenting invisible clinical target volumes with estimated uncertainties for postoperative prostate cancer radiotherapy
In postoperative radiotherapy for prostate cancer, the cancerous prosta...
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Generalizability issues with deep learning models in medicine and their potential solutions: illustrated with ConeBeam Computed Tomography (CBCT) to Computed Tomography (CT) i
Generalizability is a concern when applying a deep learning (DL) model t...
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A reinforcement learning application of guided Monte Carlo Tree Search algorithm for beam orientation selection in radiation therapy
Due to the large combinatorial problem, current beam orientation optimiz...
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Mining Domain Knowledge: Improved Framework towards Automatically Standardizing Anatomical Structure Nomenclature in Radiotherapy
Automatically standardizing nomenclature for anatomical structures in ra...
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Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose volume histogram and adversarial inspired framework for generating Pa
We propose a novel domain specific loss, which is a differentiable loss ...
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Balancing Robustness and Responsiveness in a Realtime Indoor Location System using Bluetooth Low Energy Technology and Deep Learning to Facilitate Clinical Applications
An indoor, realtime location system (RTLS) can benefit both hospitals a...
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ThreeDimensional Dose Prediction for Lung IMRT Patients with Deep Neural Networks: Robust Learning from Heterogeneous Beam Configurations
The use of neural networks to directly predict threedimensional dose di...
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Predicting Lung Nodule Malignancies by Combining Deep Convolutional Neural Network and Handcrafted Features
To predict lung nodule malignancy with a high sensitivity and specificit...
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Automatic multiobjective based feature selection for classification
Accurately classifying malignancy of lesions detected in a screening sca...
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Fully Automated Organ Segmentation in Male Pelvic CT Images
Accurate segmentation of prostate and surrounding organs at risk is impo...
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ThreeDimensional Radiotherapy Dose Prediction on Head and Neck Cancer Patients with a Hierarchically Densely Connected Unet Deep Learning Architecture
The treatment planning process for patients with head and neck (H&N) can...
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Towards automated patient data cleaning using deep learning: A feasibility study on the standardization of organ labeling
Data cleaning consumes about 80 clinical research projects. This is a mu...
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Dose Prediction with Unet: A Feasibility Study for Predicting Dose Distributions from Contours using Deep Learning on Prostate IMRT Patients
With the advancement of treatment modalities in radiation therapy, outco...
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Nonlinear Systems Identification Using Deep Dynamic Neural Networks
Neural networks are known to be effective function approximators. Recent...
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Steve Jiang
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