175 citations · 925 across the 45 of their papers we have counts for
5 papers · 1 filter
Brain Tumor Sequence Registration with Non-iterative Coarse-to-fine Networks and Dual Deep Supervision
Mingyuan Meng, Lei Bi, Dagan Feng +1
In this study, we focus on brain tumor sequence registration between pre-operative and follow-up Magnetic Resonance Imaging (MRI) scans of brain glioma patients, in the context of…
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…
Hyper-Connected Transformer Network for Multi-Modality PET-CT Segmentation
Lei Bi, Michael Fulham, Shaoli Song +2
[18F]-Fluorodeoxyglucose (FDG) positron emission tomography - computed tomography (PET-CT) has become the imaging modality of choice for diagnosing many cancers. Co-learning comple…
Automatic Tumor Segmentation via False Positive Reduction Network for Whole-Body Multi-Modal PET/CT Images
Yige Peng, Jinman Kim, Dagan Feng +1
Multi-modality Fluorodeoxyglucose (FDG) positron emission tomography / computed tomography (PET/CT) has been routinely used in the assessment of common cancers, such as lung cancer…
Non-iterative Coarse-to-fine Registration based on Single-pass Deep Cumulative Learning
Mingyuan Meng, Lei Bi, Dagan Feng +1
Deformable image registration is a crucial step in medical image analysis for finding a non-linear spatial transformation between a pair of fixed and moving images. Deep registrati…