117 citations · 183 across the 14 of their papers we have counts for
14 papers
One-for-All Adaptive Radiotherapy Planning Agent: A Foundation Framework for Daily CBCT-guided Radiotherapy
Shaoyan Pan, Kirk Jon Luca, Yuan Gao +8
In this work, we introduce the One-for-All Adaptive Radiotherapy Planning Agent, a unified foundation-model-based system that performs complete, treatment-specific online adaptive…
Dual-Energy Cone-Beam CT Using Two Orthogonal Projection Views: A Phantom Study
Junbo Peng, Tonghe Wang, Shaoyan Pan +1
This study proposes a novel imaging and reconstruction framework for dual-energy cone-beam CT (DECBCT) using only two orthogonal X-ray projections at different energy levels (2V-DE…
Patient-Specific CBCT Synthesis for Real-time Tumor Tracking in Surface-guided Radiotherapy
Shaoyan Pan, Vanessa Su, Junbo Peng +6
We present a new imaging system to support real-time tumor tracking for surface-guided radiotherapy (SGRT). SGRT uses optical surface imaging (OSI) to acquire real-time surface top…
AnatoMask: Enhancing Medical Image Segmentation with Reconstruction-guided Self-masking
Yuheng Li, Tianyu Luan, Yizhou Wu +3
Due to the scarcity of labeled data, self-supervised learning (SSL) has gained much attention in 3D medical image segmentation, by extracting semantic representations from unlabele…
Self-Supervised Adversarial Diffusion Models for Fast MRI Reconstruction
Mojtaba Safari, Zach Eidex, Shaoyan Pan +2
Purpose: To propose a self-supervised deep learning-based compressed sensing MRI (DL-based CS-MRI) method named "Adaptive Self-Supervised Consistency Guided Diffusion Model (ASSCGD…
Multi-dimension unified Swin Transformer for 3D Lesion Segmentation in Multiple Anatomical Locations
Shaoyan Pan, Yiqiao Liu, Sarah Halek +6
In oncology research, accurate 3D segmentation of lesions from CT scans is essential for the modeling of lesion growth kinetics. However, following the RECIST criteria, radiologist…
Full-dose Whole-body PET Synthesis from Low-dose PET Using High-efficiency Denoising Diffusion Probabilistic Model: PET Consistency Model
Shaoyan Pan, Elham Abouei, Junbo Peng +8
Objective: Positron Emission Tomography (PET) has been a commonly used imaging modality in broad clinical applications. One of the most important tradeoffs in PET imaging is betwee…
Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model
Shaoyan Pan, Elham Abouei, Jacob Wynne +10
Magnetic resonance imaging (MRI)-based synthetic computed tomography (sCT) simplifies radiation therapy treatment planning by eliminating the need for CT simulation and error-prone…
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…
Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT
Mingzhe Hu, Shaoyan Pan, Yuheng Li +1
In this paper, we aimed to provide a review and tutorial for researchers in the field of medical imaging using language models to improve their tasks at hand. We began by providing…
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)…