Domain Adaptation (DA) is important for deep learning-based medical imag...
Multi-organ segmentation in abdominal Computed Tomography (CT) images is...
Pretraining with large-scale 3D volumes has a potential for improving th...
Accurate segmentation of the fetal brain from Magnetic Resonance Image (...
Segmentation of pathological images is a crucial step for accurate cance...
Generalization to previously unseen images with potential domain shifts ...
Artificial Intelligence (AI) is having a tremendous impact across most a...
Background and Objective: Existing deep learning platforms for medical i...
The success of Convolutional Neural Networks (CNNs) in 3D medical image
...
Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABC...
Medical image segmentation plays an irreplaceable role in computer-assis...
Assessment of myocardial viability is essential in diagnosis and treatme...
Domain Adaptation (DA) has recently raised strong interests in the medic...
Recently, deep learning with Convolutional Neural Networks (CNNs) and
Tr...
Computed Tomography (CT) plays an important role in monitoring
radiation...
Domain generalizable model is attracting increasing attention in medical...
The segmentation of coronary arteries by convolutional neural network is...
Automatic and accurate lung nodule detection from 3D Computed Tomography...
Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN)
...
Radiotherapy is the main treatment modality for nasopharynx cancer.
Deli...
Despite that deep learning has achieved state-of-the-art performance for...
Deep learning networks have shown promising performance for accurate obj...
Gross Target Volume (GTV) segmentation plays an irreplaceable role in
ra...
Image segmentation is a fundamental topic in image processing and has be...
Deep learning-based semi-supervised learning (SSL) algorithms have led t...
Ischemic stroke lesion segmentation from Computed Tomography Perfusion (...
The segmentation of coronary arteries in X-ray angiograms by convolution...
Clinical research on smart healthcare has an increasing demand for
intel...
Automatic segmentation of vestibular schwannoma (VS) tumors from magneti...
Gliomas are the most common primary brain malignancies, with different
d...
Automatic brain tumor segmentation plays an important role for diagnosis...
Despite the state-of-the-art performance for medical image segmentation,...
Data augmentation has been widely used for training deep learning system...
One of the fundamental challenges in supervised learning for multimodal ...
Convolutional neural networks (CNNs) have achieved state-of-the-art
perf...
Medical image analysis and computer-assisted intervention problems are
i...
Deep convolutional neural networks are powerful tools for learning visua...
Accurate medical image segmentation is essential for diagnosis, surgical...