Dagan Feng
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View article: Automatic Left Ventricular Cavity Segmentation via Deep Spatial Sequential Network in 4D Computed Tomography Studies
Automatic Left Ventricular Cavity Segmentation via Deep Spatial Sequential Network in 4D Computed Tomography Studies Open
Automated segmentation of left ventricular cavity (LVC) in temporal cardiac image sequences (multiple time points) is a fundamental requirement for quantitative analysis of its structural and functional changes. Deep learning based methods…
View article: A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering
A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering Open
Medical Visual Question Answering (MedVQA) is crucial for enhancing the efficiency of clinical diagnosis by providing accurate and timely responses to clinicians' inquiries regarding medical images. Existing MedVQA models suffered from mod…
View article: 3DPX: Single Panoramic X-ray Analysis Guided by 3D Oral Structure Reconstruction
3DPX: Single Panoramic X-ray Analysis Guided by 3D Oral Structure Reconstruction Open
Panoramic X-ray (PX) is a prevalent modality in dentistry practice owing to its wide availability and low cost. However, as a 2D projection of a 3D structure, PX suffers from anatomical information loss and PX diagnosis is limited compared…
View article: SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance
SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance Open
Segmentation of infected areas in chest X-rays is pivotal for facilitating the accurate delineation of pulmonary structures and pathological anomalies. Recently, multi-modal language-guided image segmentation methods have emerged as a prom…
View article: 3DPX: Progressive 2D-to-3D Oral Image Reconstruction with Hybrid MLP-CNN Networks
3DPX: Progressive 2D-to-3D Oral Image Reconstruction with Hybrid MLP-CNN Networks Open
Panoramic X-ray (PX) is a prevalent modality in dental practice for its wide availability and low cost. However, as a 2D projection image, PX does not contain 3D anatomical information, and therefore has limited use in dental applications …
View article: Incobotulinum Toxin-A in Professional Musicians with Focal Task-Specific Dystonia: A Double Blind, Placebo Controlled, Cross-Over Study
Incobotulinum Toxin-A in Professional Musicians with Focal Task-Specific Dystonia: A Double Blind, Placebo Controlled, Cross-Over Study Open
Background: Musician’s focal task-specific dystonia is a complex disorder of fine motor control, with incomplete understanding of its etiology. There have been relatively few trials of botulinum toxin in upper limb task-specific dystonia, …
View article: Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration
Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration Open
Deformable image registration is a fundamental step for medical image analysis. Recently, transformers have been used for registration and outperformed Convolutional Neural Networks (CNNs). Transformers can capture long-range dependence am…
View article: Dynamic Traceback Learning for Medical Report Generation
Dynamic Traceback Learning for Medical Report Generation Open
Automated medical report generation has demonstrated the potential to significantly reduce the workload associated with time-consuming medical reporting. Recent generative representation learning methods have shown promise in integrating v…
View article: Enhancing medical vision-language contrastive learning via inter-matching relation modelling
Enhancing medical vision-language contrastive learning via inter-matching relation modelling Open
Medical image representations can be learned through medical vision-language contrastive learning (mVLCL) where medical imaging reports are used as weak supervision through image-text alignment. These learned image representations can be t…
View article: Full-resolution MLPs Empower Medical Dense Prediction
Full-resolution MLPs Empower Medical Dense Prediction Open
Dense prediction is a fundamental requirement for many medical vision tasks such as medical image restoration, registration, and segmentation. The most popular vision model, Convolutional Neural Networks (CNNs), has reached bottlenecks due…
View article: Efficacy and nephrotoxicity of polymyxin B in elderly patients with carbapenem resistant bacterial infection
Efficacy and nephrotoxicity of polymyxin B in elderly patients with carbapenem resistant bacterial infection Open
Background To study the efficacy and nephrotoxicity of polymyxin B in the treatment of elderly patients with carbapenem-resistant organism (CRO) infection. Methods The clinical and microbiological data of patients with CRO-infected sepsis …
View article: PET Synthesis via Self-supervised Adaptive Residual Estimation Generative Adversarial Network
PET Synthesis via Self-supervised Adaptive Residual Estimation Generative Adversarial Network Open
Positron emission tomography (PET) is a widely used, highly sensitive molecular imaging in clinical diagnosis. There is interest in reducing the radiation exposure from PET but also maintaining adequate image quality. Recent methods using …
View article: DDE: Deep Dynamic Epidemiological Modelling for Infectious Illness Development Forecasting in Multi-level Geographic Entities
DDE: Deep Dynamic Epidemiological Modelling for Infectious Illness Development Forecasting in Multi-level Geographic Entities Open
Understanding and effectively addressing the dynamics of infectious diseases, including global diseases like COVID-19, is crucial for managing the current situation and developing effective intervention strategies. Epidemiologists commonly…
View article: AutoFuse: Automatic Fusion Networks for Deformable Medical Image Registration
AutoFuse: Automatic Fusion Networks for Deformable Medical Image Registration Open
Deformable image registration aims to find a dense non-linear spatial correspondence between a pair of images, which is a crucial step for many medical tasks such as tumor growth monitoring and population analysis. Recently, Deep Neural Ne…
View article: SSPT-bpMRI: A Self-supervised Pre-training Scheme for Improving Prostate Cancer Detection and Diagnosis in Bi-parametric MRI<sup>*</sup>
SSPT-bpMRI: A Self-supervised Pre-training Scheme for Improving Prostate Cancer Detection and Diagnosis in Bi-parametric MRI<sup>*</sup> Open
Prostate cancer (PCa) is one of the most prevalent cancers in men. Early diagnosis plays a pivotal role in reducing the mortality rate from clinically significant PCa (csPCa). In recent years, bi-parametric magnetic resonance imaging (bpMR…
View article: CG-3DSRGAN: A classification guided 3D generative adversarial network for image quality recovery from low-dose PET images
CG-3DSRGAN: A classification guided 3D generative adversarial network for image quality recovery from low-dose PET images Open
Positron emission tomography (PET) is the most sensitive molecular imaging modality routinely applied in our modern healthcare. High radioactivity caused by the injected tracer dose is a major concern in PET imaging and limits its clinical…
View article: Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer
Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer Open
Survival prediction is crucial for cancer patients as it provides early prognostic information for treatment planning. Recently, deep survival models based on deep learning and medical images have shown promising performance for survival p…
View article: Deep Dynamic Epidemiological Modelling for COVID-19 Forecasting in Multi-level Districts
Deep Dynamic Epidemiological Modelling for COVID-19 Forecasting in Multi-level Districts Open
Objective: COVID-19 has spread worldwide and made a huge influence across the world. Modeling the infectious spread situation of COVID-19 is essential to understand the current condition and to formulate intervention measurements. Epidemio…
View article: A Review of Predictive and Contrastive Self-supervised Learning for Medical Images
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images Open
Over the last decade, supervised deep learning on manually annotated big data has been progressing significantly on computer vision tasks. But, the application of deep learning in medical image analysis is limited by the scarcity of high-q…
View article: AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images
AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images Open
Survival prediction is a major concern for cancer management. Deep survival models based on deep learning have been widely adopted to perform end-to-end survival prediction from medical images. Recent deep survival models achieved promisin…