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Foundation model for advancing healthcare: challenges, opportunities and future directions
Foundation model, trained on a diverse range of data and adaptable to a myriad of tasks, is
advancing healthcare. It fosters the development of healthcare artificial intelligence (AI) …
advancing healthcare. It fosters the development of healthcare artificial intelligence (AI) …
Usfm: A universal ultrasound foundation model generalized to tasks and organs towards label efficient image analysis
Inadequate generality across different organs and tasks constrains the application of
ultrasound (US) image analysis methods in smart healthcare. Building a universal US …
ultrasound (US) image analysis methods in smart healthcare. Building a universal US …
OpenMEDLab: An open-source platform for multi-modality foundation models in medicine
The emerging trend of advancing generalist artificial intelligence, such as GPTv4 and
Gemini, has reshaped the landscape of research (academia and industry) in machine …
Gemini, has reshaped the landscape of research (academia and industry) in machine …
[HTML][HTML] Integrating language into medical visual recognition and reasoning: A survey
Y Lu, A Wang - Medical Image Analysis, 2025 - Elsevier
Abstract Vision-Language Models (VLMs) are regarded as efficient paradigms that build a
bridge between visual perception and textual interpretation. For medical visual tasks, they …
bridge between visual perception and textual interpretation. For medical visual tasks, they …
Deblurring masked image modeling for ultrasound image analysis
Recently, large pretrained vision foundation models based on masked image modeling
(MIM) have attracted unprecedented attention and achieved remarkable performance across …
(MIM) have attracted unprecedented attention and achieved remarkable performance across …
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 …
Breast tumor classification based on self-supervised contrastive learning from ultrasound videos
Y Tang, S Tang, J Zhang, H Chen - arxiv preprint arxiv:2408.10600, 2024 - arxiv.org
Background: Breast ultrasound is prominently used in diagnosing breast tumors. At present,
many automatic systems based on deep learning have been developed to help radiologists …
many automatic systems based on deep learning have been developed to help radiologists …
A novel open-source ultrasound dataset with deep learning benchmarks for spinal cord injury localization and anatomical segmentation
While deep learning has catalyzed breakthroughs across numerous domains, its broader
adoption in clinical settings is inhibited by the costly and time-intensive nature of data …
adoption in clinical settings is inhibited by the costly and time-intensive nature of data …
[PDF][PDF] Ultramae: Multi-modal masked autoencoder for ultrasound pre-training
Pre-training on a large dataset such as ImageNet followed by supervised fine-tuning has
brought success in various deep learning-based tasks. However, the modalities of natural …
brought success in various deep learning-based tasks. However, the modalities of natural …
:~Cataract Surgical Masked Autoencoder (MAE) based Pre-training
Automated analysis of surgical videos is crucial for improving surgical training, workflow
optimization, and postoperative assessment. We introduce a CSMAE, Masked Autoencoder …
optimization, and postoperative assessment. We introduce a CSMAE, Masked Autoencoder …