67 citations · 385 across the 32 of their papers we have counts for
14 papers · 1 filter
Really Need Recursion? Revisiting One-pass Registration with Multi-level Multi-space Contextual Guidance
Yue Lin, Shenghai Wu, Mingyuan Meng
Deformable image registration is a fundamental challenge in medical image analysis. Recent deep learning-based methods typically adopt either one-pass architectures that complete r…
Case-Specific Priors-Guided Multimodal Fusion for Prognosis Prediction in Head and Neck Cancer
Yue Lin, Shuchang Ye, Shenghai Wu +2
Accurate prognosis prediction for head and neck cancer typically necessitates integrating highly heterogeneous clinical and pathological evidence by sophisticated multimodal fusion…
Advancing Deformable Medical Image Registration with Multi-axis Cross-covariance Attention
Mingyuan Meng, Michael Fulham, Lei Bi +1
Deformable image registration is a fundamental requirement for medical image analysis. Recently, transformers have been widely used in deep learning-based registration methods for…
3DPX: Single Panoramic X-ray Analysis Guided by 3D Oral Structure Reconstruction
Xiaoshuang Li, Zimo Huang, Mingyuan Meng +7
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 anato…
3DPX: Progressive 2D-to-3D Oral Image Reconstruction with Hybrid MLP-CNN Networks
Xiaoshuang Li, Mingyuan Meng, Zimo Huang +5
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 informa…
Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration
Mingyuan Meng, Dagan Feng, Lei Bi +1
Deformable image registration is a fundamental step for medical image analysis. Recently, transformers have been used for registration and outperformed Convolutional Neural Network…
Full-resolution MLPs Empower Medical Dense Prediction
Mingyuan Meng, Yuxin Xue, Dagan Feng +2
Dense prediction is a fundamental requirement for many medical vision tasks such as medical image restoration, registration, and segmentation. The most popular vision model, Convol…
AutoFuse: Automatic Fusion Networks for Deformable Medical Image Registration
Mingyuan Meng, Michael Fulham, Dagan Feng +2
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 m…
Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer
Mingyuan Meng, Lei Bi, Michael Fulham +2
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 med…
AdaMSS: Adaptive Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images
Mingyuan Meng, Bingxin Gu, Michael Fulham +4
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 me…
Radiomics-enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer
Mingyuan Meng, Lei Bi, Dagan Feng +1
Outcome prediction is crucial for head and neck cancer patients as it can provide prognostic information for early treatment planning. Radiomics methods have been widely used for o…
The Brain Tumor Sequence Registration (BraTS-Reg) Challenge: Establishing Correspondence Between Pre-Operative and Follow-up MRI Scans of Diffuse Glioma Patients
Bhakti Baheti, Satrajit Chakrabarty, Hamed Akbari +70
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been progress in developing gene…
DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CT
Mingyuan Meng, Bingxin Gu, Lei Bi +3
Nasopharyngeal Carcinoma (NPC) is a malignant epithelial cancer arising from the nasopharynx. Survival prediction is a major concern for NPC patients, as it provides early prognost…
Prediction of 5-year Progression-Free Survival in Advanced Nasopharyngeal Carcinoma with Pretreatment PET/CT using Multi-Modality Deep Learning-based Radiomics
Bingxin Gu, Mingyuan Meng, Lei Bi +3
Objective: Deep Learning-based Radiomics (DLR) has achieved great success in medical image analysis and has been considered a replacement for conventional radiomics that relies on…