Masked Image Modeling: A Survey
In this work, we survey recent studies on masked image modeling (MIM), an approach that
emerged as a powerful self-supervised learning technique in computer vision. The MIM task …
emerged as a powerful self-supervised learning technique in computer vision. The MIM task …
Kernel Masked Image Modeling Through the Lens of Theoretical Understanding
Masked image modeling (MIM) has been considered as the state-of-the-art (SOTA) self-
supervised learning (SSL) technique in terms of visual pretraining. The impressive …
supervised learning (SSL) technique in terms of visual pretraining. The impressive …
Gallbladder cancer detection via ultrasound image analysis: An end‐to‐end hierarchical feature‐fused model
Gallbladder cancer is a fatal disease, and its early diagnosis can significantly impact patient
treatment. Ultrasound imaging is often the initial diagnostic test for gallbladder cancer …
treatment. Ultrasound imaging is often the initial diagnostic test for gallbladder cancer …
Privacy-Preserving Federated Foundation Model for Generalist Ultrasound Artificial Intelligence
Ultrasound imaging is widely used in clinical diagnosis due to its non-invasive nature and
real-time capabilities. However, conventional ultrasound diagnostics face several limitations …
real-time capabilities. However, conventional ultrasound diagnostics face several limitations …
LQ-Adapter: ViT-Adapter with Learnable Queries for Gallbladder Cancer Detection from Ultrasound Image
We focus on the problem of Gallbladder Cancer (GBC) detection from Ultrasound (US)
images. The problem presents unique challenges to modern Deep Neural Network (DNN) …
images. The problem presents unique challenges to modern Deep Neural Network (DNN) …
URFM: a general Ultrasound Representation Foundation Model for advancing ultrasound image diagnosis
Ultrasound imaging is pivotal in clinical diagnostics, providing critical insights into a wide
range of diseases and organs. However, advancing artificial intelligence (AI) in this field is …
range of diseases and organs. However, advancing artificial intelligence (AI) in this field is …