666 citations · 972 across the 30 of their papers we have counts for
31 papers
One-step Iterative Estimation of Effective Atomic Number and Electron Density for Dual Energy CT
Qian Wang, Huiqiao Xie, Tonghe Wang +7
Dual-energy computed tomography (DECT) is a promising technology that has shown a number of clinical advantages over conventional X-ray CT, such as improved material identification…
Data-Driven Volumetric Image Generation from Surface Structures using a Patient-Specific Deep Leaning Model
Shaoyan Pan, Chih-Wei Chang, Marian Axente +5
The advent of computed tomography significantly improves patient health regarding diagnosis, prognosis, and treatment planning and verification. However, tomographic imaging escala…
Cross-Shaped Windows Transformer with Self-supervised Pretraining for Clinically Significant Prostate Cancer Detection in Bi-parametric MRI
Yuheng Li, Jacob Wynne, Jing Wang +8
Biparametric magnetic resonance imaging (bpMRI) has demonstrated promising results in prostate cancer (PCa) detection using convolutional neural networks (CNNs). Recently, transfor…
Cycle-guided Denoising Diffusion Probability Model for 3D Cross-modality MRI Synthesis
Shaoyan Pan, Chih-Wei Chang, Junbo Peng +7
This study aims to develop a novel Cycle-guided Denoising Diffusion Probability Model (CG-DDPM) for cross-modality MRI synthesis. The CG-DDPM deploys two DDPMs that condition each…
Deep Learning in MRI-guided Radiation Therapy: A Systematic Review
Zach Eidex, Yifu Ding, Jing Wang +5
MRI-guided radiation therapy (MRgRT) offers a precise and adaptive approach to treatment planning. Deep learning applications which augment the capabilities of MRgRT are systematic…
Denoising Magnetic Resonance Spectroscopy (MRS) Data Using Stacked Autoencoder for Improving Signal-to-Noise Ratio and Speed of MRS
Jing Wang, Bing Ji, Yang Lei +3
Background: Magnetic resonance spectroscopy (MRS) enables non-invasive detection and measurement of biochemicals and metabolites. However, MRS has low signal-to-noise ratio (SNR) w…
CBCT-Based Synthetic CT Image Generation Using Conditional Denoising Diffusion Probabilistic Model
Junbo Peng, Richard L. J. Qiu, Jacob F Wynne +8
Background: Daily or weekly cone-beam computed tomography (CBCT) scans are commonly used for accurate patient positioning during the image-guided radiotherapy (IGRT) process, makin…
Deep Learning-based Multi-Organ CT Segmentation with Adversarial Data Augmentation
Shaoyan Pan, Shao-Yuan Lo, Min Huang +5
In this work, we propose an adversarial attack-based data augmentation method to improve the deep-learning-based segmentation algorithm for the delineation of Organs-At-Risk (OAR)…
A Retrospective Study on the Investigation of Potential Clinical Benefits of Online Adaptive Proton Therapy for Head and Neck Cancer
Chih-Wei Chang, Duncan Bohannon, Zhen Tian +6
Online adaptive proton therapy (APT) is an ideal solution theoretically, which however is challenging to proton clinics. Although multiple groups have been endeavoring to develop o…
Deep Learning-based Protoacoustic Signal Denoising for Proton Range Verification
Jing Wang, James J. Sohn, Yang Lei +5
Objective: Proton therapy offers an advantageous dose distribution compared to the photon therapy, since it deposits most of the energy at the end of range, namely the Bragg peak (…
Early in vivo Radiation Damage Quantification for Pediatric Craniospinal Irradiation Using Longitudinal MRI for Intensity Modulated Proton Therapy
Chih-Wei Chang, Matt Goette, Nadja Kadom +8
Purpose: Proton vertebral body sparing craniospinal irradiation (VBS CSI) treats the thecal sac while avoiding the anterior vertebral bodies in effort to reduce myelosuppression an…
Deep learning-based Fast Volumetric Image Generation for Image-guided Proton FLASH Radiotherapy
Chih-Wei Chang, Yang Lei, Tonghe Wang +7
Proton FLASH therapy leverages ultra-high dose-rate radiation to enhance the sparing of organs at risk without compromising tumor control probability. To prepare for the delivery o…
Landmark Tracking in Liver US images Using Cascade Convolutional Neural Networks with Long Short-Term Memory
Yupei Zhang, Xianjin Dai, Zhen Tian +6
This study proposed a deep learning-based tracking method for ultrasound (US) image-guided radiation therapy. The proposed cascade deep learning model is composed of an attention n…
Feasibility Study of Hybrid Inverse Planning with Transmission Beams and Single-energy Spread-out Bragg Peaks for Proton Flash Radiotherapy
Chaoqiong Ma, Xiaofeng Yang, Chih-Wei Chang +6
Ultra-high dose rate (FLASH) proton planning with only transmission beams (TBs) has limitations in normal tissue sparing. The single-energy spread-out Bragg peaks (SESOBPs) of FLAS…
Deformable Image Registration using Unsupervised Deep Learning for CBCT-guided Abdominal Radiotherapy
Huiqiao Xie, Yang Lei, Yabo Fu +6
CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fraction…
Multimodal Imaging-based Material Mass Density Estimation for Proton Therapy Using Physics-Constrained Deep Learning
Chih-Wei Chang, Raanan Marants, Yuan Gao +7
Mapping computed tomography (CT) number to material property dominates the proton range uncertainty. This work aims to develop a physics-constrained deep learning-based multimodal…
Reinforcement Learning in Medical Image Analysis: Concepts, Applications, Challenges, and Future Directions
Mingzhe Hu, Jiahan Zhang, Luke Matkovic +2
Motivation: Medical image analysis involves tasks to assist physicians in qualitative and quantitative analysis of lesions or anatomical structures, significantly improving the acc…
Automatic Inverse Treatment Planning for Gamma Knife Radiosurgery via Deep Reinforcement Learning
Yingzi Liu, Chenyang Shen, Tonghe Wang +6
Purpose: Several inverse planning algorithms have been developed for Gamma Knife (GK) radiosurgery to determine a large number of plan parameters via solving an optimization proble…
Artificial Intelligence in Tumor Subregion Analysis Based on Medical Imaging: A Review
Mingquan Lin, Jacob Wynne, Yang Lei +4
Medical imaging is widely used in cancer diagnosis and treatment, and artificial intelligence (AI) has achieved tremendous success in various tasks of medical image analysis. This…
Generative Adversarial Network for Image Synthesis
Yang Lei, Richard L. J. Qiu, Tonghe Wang +3
This chapter reviews recent developments of generative adversarial networks (GAN)-based methods for medical and biomedical image synthesis tasks. These methods are classified into…
Synthetic MRI-aided Head-and-Neck Organs-at-Risk Auto-Delineation for CBCT-guided Adaptive Radiotherapy
Xianjin Dai, Yang Lei, Tonghe Wang +7
Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-va…
Knowledge-based Radiation Treatment Planning: A Data-driven Method Survey
Shadab Momin, Yabo Fu, Yang Lei +5
This paper surveys the data-driven dose prediction approaches introduced for knowledge-based planning (KBP) in the last decade. These methods were classified into two major categor…
An institutional study on plan quality and variation of manual forward planning for Gamma Knife radiosurgery for vestibular schwannoma
Zhen Tian, Tonghe Wang, Xiaofeng Yang +5
Due to the complexity and cumbersomeness of Gamma Knife (GK) manual forward planning, the quality of the resulting treatment plans heavily depends on the planners skill, experience…
A plan quality control method of treatment planning for Gamma Knife radiosurgery
Tonghe Wang, Matt D. Giles, Elizabeth Butker +5
With many variables to adjust, conventional manual forward planning for Gamma Knife (GK) radiosurgery is very complicated and cumbersome. The resulting plan quality heavily depends…