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Machine Learning Techniques for Quantification of Knee Segmentation from MRI
Joint Authors
More, Sujeet
Singla, Jimmy
Abugabah, Ahed
AlZubi, Ahmad Ali
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-07
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Magnetic resonance imaging (MRI) is precise and efficient for interpreting the soft and hard tissues.
Moreover, for the detailed diagnosis of varied diseases such as knee rheumatoid arthritis (RA), segmentation of the knee magnetic resonance image is a challenging and complex task that has been explored broadly.
However, the accuracy and reproducibility of segmentation approaches may require prior extraction of tissues from MR images.
The advances in computational methods for segmentation are reliant on several parameters such as the complexity of the tissue, quality, and acquisition process involved.
This review paper focuses and briefly describes the challenges faced by segmentation techniques from magnetic resonance images followed by an overview of diverse categories of segmentation approaches.
The review paper also focuses on automatic approaches and semiautomatic approaches which are extensively used with performance metrics and sufficient achievement for clinical trial assistance.
Furthermore, the results of different approaches related to MR sequences used to image the knee tissues and future aspects of the segmentation are discussed.
American Psychological Association (APA)
More, Sujeet& Singla, Jimmy& Abugabah, Ahed& AlZubi, Ahmad Ali. 2020. Machine Learning Techniques for Quantification of Knee Segmentation from MRI. Complexity،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1143014
Modern Language Association (MLA)
More, Sujeet…[et al.]. Machine Learning Techniques for Quantification of Knee Segmentation from MRI. Complexity No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1143014
American Medical Association (AMA)
More, Sujeet& Singla, Jimmy& Abugabah, Ahed& AlZubi, Ahmad Ali. Machine Learning Techniques for Quantification of Knee Segmentation from MRI. Complexity. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1143014
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143014