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Methods for the segmentation and classification of breast ultrasound images: a review
- Source :
- J Ultrasound
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- PURPOSE: Breast ultrasound (BUS) is one of the imaging modalities for the diagnosis and treatment of breast cancer. However, the segmentation and classification of BUS images is a challenging task. In recent years, several methods for segmenting and classifying BUS images have been studied. These methods use BUS datasets for evaluation. In addition, semantic segmentation algorithms have gained prominence for segmenting medical images. METHODS: In this paper, we examined different methods for segmenting and classifying BUS images. Popular datasets used to evaluate BUS images and semantic segmentation algorithms were examined. Several segmentation and classification papers were selected for analysis and review. Both conventional and semantic methods for BUS segmentation were reviewed. RESULTS: Commonly used methods for BUS segmentation were depicted in a graphical representation, while other conventional methods for segmentation were equally elucidated. CONCLUSIONS: We presented a review of the segmentation and classification methods for tumours detected in BUS images. This review paper selected old and recent studies on segmenting and classifying tumours in BUS images.
- Subjects :
- ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Breast Neoplasms
02 engineering and technology
030218 nuclear medicine & medical imaging
Imaging modalities
03 medical and health sciences
0302 clinical medicine
Market segmentation
0202 electrical engineering, electronic engineering, information engineering
Internal Medicine
Humans
Medicine
Radiology, Nuclear Medicine and imaging
Segmentation
Breast ultrasound
Review Paper
medicine.diagnostic_test
business.industry
technology, industry, and agriculture
Representation (systemics)
Pattern recognition
General Medicine
ComputingMethodologies_PATTERNRECOGNITION
Classification methods
Female
020201 artificial intelligence & image processing
Ultrasonography, Mammary
Artificial intelligence
business
human activities
Algorithms
Subjects
Details
- ISSN :
- 18767931
- Volume :
- 24
- Database :
- OpenAIRE
- Journal :
- Journal of Ultrasound
- Accession number :
- edsair.doi.dedup.....e2c521b62a569361c32f6b0e1399220c