Masked Modeling-Based Ultrasound Image Classification via Self-Supervised Learning
Recently, deep learning-based methods have emerged as the preferred approach for ultrasound data analysis. However, these methods often require large-scale annotated datasets for training deep models, which are not readily available in practical scenarios. Additionally, the presence of speckle noise...
Saved in:
Main Authors: | Kele Xu, Kang You, Boqing Zhu, Ming Feng, Dawei Feng, Cheng Yang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Open Journal of Engineering in Medicine and Biology |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10463101/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation
by: Feng Wei, et al.
Published: (2024-12-01) -
Self-supervised speech representation learning based on positive sample comparison and masking reconstruction
by: Wenlin ZHANG, et al.
Published: (2022-07-01) -
Toward accurate hand mesh estimation via masked image modeling
by: Yanli Li, et al.
Published: (2025-01-01) -
Supervised contrastive pre-training models for mammography screening
by: Zhenjie Cao, et al.
Published: (2025-02-01) -
Semi-supervised Gaussian process classification algorithm addressing the class imbalance
by: Zhan-guo XIA, et al.
Published: (2013-05-01)