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Semi-supervised Learning for Real-time Segmentation of Ultrasound Video Objects: A Review
- Source :
- Advanced Ultrasound in Diagnosis and Therapy, Vol 7, Iss 4, Pp 333-347 (2023)
- Publication Year :
- 2023
- Publisher :
- Editorial Office of Advanced Ultrasound in Diagnosis and Therapy, 2023.
-
Abstract
- Real-time intelligent segmentation of ultrasound video object is a demanding task in the field of medical image processing and serves as an essential and critical step in image-guided clinical procedures. However, obtaining reliable and accurate medical image annotations often necessitates expert guidance, making the acquisition of large-scale annotated datasets challenging and costly. This presents obstacles for traditional supervised learning methods. Consequently, semi-supervised learning (SSL) has emerged as a promising solution, capable of utilizing unlabeled data to enhance model performance and has been widely adopted in medical image segmentation tasks. However, striking a balance between segmentation accuracy and inference speed remains a challenge for real-time segmentation. This paper provides a comprehensive review of research progress in real-time intelligent semi-supervised ultrasound video object segmentation (SUVOS) and offers insights into future developments in this area.
Details
- Language :
- English
- ISSN :
- 25762516
- Volume :
- 7
- Issue :
- 4
- Database :
- Directory of Open Access Journals
- Journal :
- Advanced Ultrasound in Diagnosis and Therapy
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.b9fa9e3256c4e2faa499b17d7d8053f
- Document Type :
- article
- Full Text :
- https://doi.org/10.37015/AUDT.2023.230016