Domain Adaptation (DA) is important for deep learning-based medical imag...
Multi-organ segmentation in abdominal Computed Tomography (CT) images is...
Although deep learning have revolutionized abdominal multi-organ
segment...
The Segment Anything Model (SAM) represents a state-of-the-art research
...
There is an increasing interest in developing LLMs for medical diagnosis...
The accurate diagnosis on pathological subtypes for lung cancer is of
si...
The recent surge of foundation models in computer vision and natural lan...
Survival outcome assessment is challenging and inherently associated wit...
Pretraining with large-scale 3D volumes has a potential for improving th...
Foundation models have exhibited remarkable success in various applicati...
Deep learning models often require large amounts of data for training,
l...
Accurate segmentation of the fetal brain from Magnetic Resonance Image (...
This article discusses the opportunities, applications and future direct...
A major enduring focus of clinical workflows is disease analytics and
di...
Local hemodynamic forces play an important role in determining the funct...
Large pre-trained vision-language models have shown great prominence in
...
Segmentation of pathological images is a crucial step for accurate cance...
The Segment Anything Model (SAM) made an eye-catching debut recently and...
Large-scale models pre-trained on large-scale datasets have profoundly
a...
Inevitable domain and task discrepancies in real-world scenarios can imp...
Generalization to previously unseen images with potential domain shifts ...
Background and Objective: Existing deep learning platforms for medical i...
The success of Convolutional Neural Networks (CNNs) in 3D medical image
...
Neural architecture search (NAS) algorithms save tremendous labor from h...
Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABC...
Medical image segmentation plays an irreplaceable role in computer-assis...
Image-based characterization and disease understanding involve integrati...
Medical image segmentation has been widely recognized as a pivot procedu...
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...
Precise localization of polyp is crucial for early cancer screening in
g...
Weak supervision learning on classification labels has demonstrated high...
The recent vision transformer(i.e.for image classification) learns non-l...
Deep learning has demonstrated significant improvements in medical image...
The study of multi-type Protein-Protein Interaction (PPI) is fundamental...
Automatic and accurate lung nodule detection from 3D Computed Tomography...
Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN)
...
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...
Aggregating multi-level feature representation plays a critical role in
...
Deep learning-based semi-supervised learning (SSL) algorithms have led t...
Multi-organ segmentation has extensive applications in many clinical
app...
Nuclei segmentation is a fundamental task in histopathology image analys...
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...
Recently, deep neural networks have demonstrated comparable and even bet...