20 citations · 46 across the 4 of their papers we have counts for
4 papers
Segment Anything Model for Medical Image Segmentation: Current Applications and Future Directions
Yichi Zhang, Zhenrong Shen, Rushi Jiao
Due to the inherent flexibility of prompting, foundation models have emerged as the predominant force in the fields of natural language processing and computer vision. The recent i…
Towards Segment Anything Model (SAM) for Medical Image Segmentation: A Survey
Yichi Zhang, Rushi Jiao
Due to the flexibility of prompting, foundation models have become the dominant force in the domains of natural language processing and image generation. With the recent introducti…
Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation
Rushi Jiao, Yichi Zhang, Le Ding +2
Medical image segmentation is a fundamental and critical step in many image-guided clinical approaches. Recent success of deep learning-based segmentation methods usually relies on…
Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation
Yichi Zhang, Rushi Jiao, Qingcheng Liao +2
Medical image segmentation is a fundamental and critical step in many clinical approaches. Semi-supervised learning has been widely applied to medical image segmentation tasks sinc…