Richard L. J. Qiu
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View article: Trackerless 3D ultrasound volume reconstruction from 2D freehand scans using a hybrid transformer–CNN framework
Trackerless 3D ultrasound volume reconstruction from 2D freehand scans using a hybrid transformer–CNN framework Open
Background Generating three‐dimensional (3D) ultrasound (US) data from conventional two‐dimensional (2D) freehand acquisitions typically necessitates external tracking systems to ascertain probe positioning. However, these hardware‐based s…
View article: Res-MoCoDiff: residual-guided diffusion models for motion artifact correction in brain MRI
Res-MoCoDiff: residual-guided diffusion models for motion artifact correction in brain MRI Open
Objective. Motion artifacts (ARTs) in brain magnetic resonance imaging (MRI), mainly from rigid head motion, degrade image quality and hinder downstream applications. Conventional methods to mitigate these ARTs, including repeated acquisit…
View article: Clinically Interpretable Survival Risk Stratification in Head and Neck Cancer Using Bayesian Networks and Markov Blankets
Clinically Interpretable Survival Risk Stratification in Head and Neck Cancer Using Bayesian Networks and Markov Blankets Open
View article: Foundation model based multimodal transformer framework for survival analysis in HER2 stratified breast cancer
Foundation model based multimodal transformer framework for survival analysis in HER2 stratified breast cancer Open
Objective . To improve survival prediction for HER2-positive breast cancer by integrating histopathological, molecular, and clinical data using a multimodal transformer framework. Approach . We propose a multimodal transformer framework fo…
View article: Res-MoCoDiff: Residual-guided diffusion models for motion artifact correction in brain MRI.
Res-MoCoDiff: Residual-guided diffusion models for motion artifact correction in brain MRI. Open
Res-MoCoDiff offers a robust and efficient solution for correcting MRI motion artifacts, preserving fine structural details while significantly reducing computational overhead. Its speed and restoration fidelity underscore its potential fo…
View article: Asymmetry in neurovascular bundle blood flow in prostate cancer patients: A pre‐treatment doppler ultrasound study
Asymmetry in neurovascular bundle blood flow in prostate cancer patients: A pre‐treatment doppler ultrasound study Open
Background Neurovascular‐sparing treatment is believed to help preserve erectile function for localized prostate cancer, given the key role of the arterial supply of neurovascular bundles (NVBs) in potency recovery post‐treatment. While NV…
View article: Current progress of digital twin construction using medical imaging
Current progress of digital twin construction using medical imaging Open
Medical imaging is fundamental to digital twin technology, enabling patient‐specific virtual models of anatomy and physiology. By integrating high‐resolution modalities (Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron …
View article: DINOv3 with Test-Time Training for Medical Image Registration
DINOv3 with Test-Time Training for Medical Image Registration Open
Prior medical image registration approaches, particularly learning-based methods, often require large amounts of training data, which constrains clinical adoption. To overcome this limitation, we propose a training-free pipeline that relie…
View article: Advancing MRI reconstruction: A systematic review of deep learning and compressed sensing integration
Advancing MRI reconstruction: A systematic review of deep learning and compressed sensing integration Open
View article: STAT3 and the resistance ability of HSC to ionizing radiation
STAT3 and the resistance ability of HSC to ionizing radiation Open
HSC is a very important part of the blood system and has a functional transcription factor, STAT3. When STAT3 is damaged, it is very likely to lead to death of HSC and even the whole organism. The ionizing radiation, on the other hand, is …
View article: Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle dual-energy cone-beam CT
Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle dual-energy cone-beam CT Open
Objective . Limited-angle dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, its clinical implementations are …
View article: MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shifting Open
Objective. Magnetic resonance imaging (MRI) is essential in clinical and research contexts, providing exceptional soft-tissue contrast. However, prolonged acquisition times often lead to patient discomfort and motion artifacts. Diffusion-b…
View article: A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning
A Large Convolutional Neural Network for Clinical Target and Multi-organ Segmentation in Gynecologic Brachytherapy with Multi-stage Learning Open
Purpose: Accurate segmentation of clinical target volumes (CTV) and organs-at-risk is crucial for optimizing gynecologic brachytherapy (GYN-BT) treatment planning. However, anatomical variability, low soft-tissue contrast in CT imaging, an…
View article: CT-guided CBCT multi-organ segmentation using a multi-channel conditional consistency diffusion model for lung cancer radiotherapy
CT-guided CBCT multi-organ segmentation using a multi-channel conditional consistency diffusion model for lung cancer radiotherapy Open
In cone beam computed tomography (CBCT)-guided adaptive radiotherapy, rapid and precise segmentation of organs-at-risk (OARs) is essential for accurate dose verification and online replanning. The quality of CBCT images obtained with curre…
View article: Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging
Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging Open
Vision foundation models (VFMs) are pre-trained on extensive image datasets to learn general representations for diverse types of data. These models can subsequently be fine-tuned for specific downstream tasks, significantly boosting perfo…
View article: A review of artificial intelligence in brachytherapy
A review of artificial intelligence in brachytherapy Open
Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachyther…
View article: STAT3 and the resistance ability of HSC to ionizing radiation
STAT3 and the resistance ability of HSC to ionizing radiation Open
HSC is a very important part of the blood system and has a functional transcription factor, STAT3. When STAT3 is damaged, it is very likely to lead to death of HSC and even the whole organism. The ionizing radiation, on the other hand, is …
View article: Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging
Triad: Vision Foundation Model for 3D Magnetic Resonance Imaging Open
Vision foundation models (VFMs) are pre-trained on extensive image datasets to learn general representations for diverse types of data. These models can subsequently be fine-tuned for specific downstream tasks, significantly boosting perfo…
View article: Evaluation and failure analysis of four commercial deep learning‐based autosegmentation software for abdominal organs at risk
Evaluation and failure analysis of four commercial deep learning‐based autosegmentation software for abdominal organs at risk Open
Purpose Deep learning‐based segmentation of organs‐at‐risk (OAR) is emerging to become mainstream in clinical practice because of the superior performance over atlas and model‐based autocontouring methods. While several commercial deep lea…
View article: Exploration of an adaptive proton therapy strategy using CBCT with the concept of digital twins
Exploration of an adaptive proton therapy strategy using CBCT with the concept of digital twins Open
Objective. This study aims to develop a digital twin (DT) framework to achieve adaptive proton prostate stereotactic body radiation therapy (SBRT) with fast treatment plan selection and patient-specific clinical target volume (CTV) setup u…
View article: Temporally Corrected Dose Accumulation – Next Steps in the Biology of Reirradiation
Temporally Corrected Dose Accumulation – Next Steps in the Biology of Reirradiation Open
View article: Unsupervised Bayesian generation of synthetic CT from CBCT using patient‐specific score‐based prior
Unsupervised Bayesian generation of synthetic CT from CBCT using patient‐specific score‐based prior Open
Background Cone‐beam computed tomography (CBCT) scans, performed fractionally (e.g., daily or weekly), are widely utilized for patient alignment in the image‐guided radiotherapy (IGRT) process, thereby making it a potential imaging modalit…
View article: Machine learning in image‐based outcome prediction after radiotherapy: A review
Machine learning in image‐based outcome prediction after radiotherapy: A review Open
The integration of machine learning (ML) with radiotherapy has emerged as a pivotal innovation in outcome prediction, bringing novel insights amid unique challenges. This review comprehensively examines the current scope of ML applications…
View article: Current Progress of Digital Twin Construction Using Medical Imaging
Current Progress of Digital Twin Construction Using Medical Imaging Open
Medical imaging has played a pivotal role in advancing and refining digital twin technology, allowing for the development of highly personalized virtual models that represent human anatomy and physiological functions. A key component in co…
View article: Optimization-Based Image Reconstruction Regularized with Inter-Spectral Structural Similarity for Limited-Angle Dual-Energy Cone-Beam CT
Optimization-Based Image Reconstruction Regularized with Inter-Spectral Structural Similarity for Limited-Angle Dual-Energy Cone-Beam CT Open
Background: Limited-angle (LA) dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, its clinical implementations…
View article: T1-contrast Enhanced MRI Generation from Multi-parametric MRI for Glioma Patients with Latent Tumor Conditioning
T1-contrast Enhanced MRI Generation from Multi-parametric MRI for Glioma Patients with Latent Tumor Conditioning Open
Objective: Gadolinium-based contrast agents (GBCAs) are commonly used in MRI scans of patients with gliomas to enhance brain tumor characterization using T1-weighted (T1W) MRI. However, there is growing concern about GBCA toxicity. This st…
View article: Prediction of early recurrence of adult‐type diffuse gliomas following radiotherapy using multi‐modal magnetic resonance images
Prediction of early recurrence of adult‐type diffuse gliomas following radiotherapy using multi‐modal magnetic resonance images Open
Background Adult‐type diffuse gliomas are among the central nervous system's most aggressive malignant primary neoplasms. Despite advancements in systemic therapies and technological improvements in radiation oncology treatment delivery, t…
View article: CT-based synthetic contrast-enhanced dual-energy CT generation using conditional denoising diffusion probabilistic model
CT-based synthetic contrast-enhanced dual-energy CT generation using conditional denoising diffusion probabilistic model Open
Objective. The study aimed to generate synthetic contrast-enhanced Dual-energy CT (CE-DECT) images from non-contrast single-energy CT (SECT) scans, addressing the limitations posed by the scarcity of DECT scanners and the health risks asso…
View article: Deep Learning Based Apparent Diffusion Coefficient Map Generation from Multi-parametric MR Images for Patients with Diffuse Gliomas
Deep Learning Based Apparent Diffusion Coefficient Map Generation from Multi-parametric MR Images for Patients with Diffuse Gliomas Open
Purpose: Apparent diffusion coefficient (ADC) maps derived from diffusion weighted (DWI) MRI provides functional measurements about the water molecules in tissues. However, DWI is time consuming and very susceptible to image artifacts, lea…
View article: Self-Supervised Adversarial Diffusion Models for Fast MRI Reconstruction
Self-Supervised Adversarial Diffusion Models for Fast MRI Reconstruction Open
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)" to accelerate data acquisition without requiring fully s…