[HTML][HTML] Review of large vision models and visual prompt engineering

J Wang, Z Liu, L Zhao, Z Wu, C Ma, S Yu, H Dai… - Meta-Radiology, 2023 - Elsevier
Visual prompt engineering is a fundamental methodology in the field of visual and image
artificial general intelligence. As the development of large vision models progresses, the …

On the challenges and perspectives of foundation models for medical image analysis

S Zhang, D Metaxas - Medical image analysis, 2024 - Elsevier
This article discusses the opportunities, applications and future directions of large-scale
pretrained models, ie, foundation models, which promise to significantly improve the …

Segment anything in medical images

J Ma, Y He, F Li, L Han, C You, B Wang - Nature Communications, 2024 - nature.com
Medical image segmentation is a critical component in clinical practice, facilitating accurate
diagnosis, treatment planning, and disease monitoring. However, existing methods, often …

Sam 2: Segment anything in images and videos

N Ravi, V Gabeur, YT Hu, R Hu, C Ryali, T Ma… - arxiv preprint arxiv …, 2024 - arxiv.org
We present Segment Anything Model 2 (SAM 2), a foundation model towards solving
promptable visual segmentation in images and videos. We build a data engine, which …

Segment anything model for medical image analysis: an experimental study

MA Mazurowski, H Dong, H Gu, J Yang, N Konz… - Medical Image …, 2023 - Elsevier
Training segmentation models for medical images continues to be challenging due to the
limited availability of data annotations. Segment Anything Model (SAM) is a foundation …

Segment anything model for medical images?

Y Huang, X Yang, L Liu, H Zhou, A Chang, X Zhou… - Medical Image …, 2024 - Elsevier
Abstract The Segment Anything Model (SAM) is the first foundation model for general image
segmentation. It has achieved impressive results on various natural image segmentation …

Medical sam adapter: Adapting segment anything model for medical image segmentation

J Wu, W Ji, Y Liu, H Fu, M Xu, Y Xu, Y ** - arxiv preprint arxiv:2304.12620, 2023 - arxiv.org
The Segment Anything Model (SAM) has recently gained popularity in the field of image
segmentation due to its impressive capabilities in various segmentation tasks and its prompt …

Samrs: Scaling-up remote sensing segmentation dataset with segment anything model

D Wang, J Zhang, B Du, M Xu, L Liu… - Advances in Neural …, 2023 - proceedings.neurips.cc
The success of the Segment Anything Model (SAM) demonstrates the significance of data-
centric machine learning. However, due to the difficulties and high costs associated with …

Ma-sam: Modality-agnostic sam adaptation for 3d medical image segmentation

C Chen, J Miao, D Wu, A Zhong, Z Yan, S Kim… - Medical Image …, 2024 - Elsevier
Abstract The Segment Anything Model (SAM), a foundation model for general image
segmentation, has demonstrated impressive zero-shot performance across numerous …

Efficientsam: Leveraged masked image pretraining for efficient segment anything

Y **ong, B Varadarajan, L Wu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract Segment Anything Model (SAM) has emerged as a powerful tool for numerous
vision applications. A key component that drives the impressive performance for zero-shot …