Ketki C Pathak* and Sejal Patel

Electronics and Communicating Engineering Department, Sarvajanik College of Engineering and Technology, Gujarat Technological University, India

*Corresponding Author:Ketki C Pathak, Electronics and Communicating Engineering Department, Sarvajanik College of Engineering and Technology, Gujarat Technological University, India.

Received: June 30, 2022; Published: November 12, 2022

Abstract

Image segmentation is the problem of partitioning an image into meaningful parts, often consisting of an object and background. As an important part of many imaging applications, e.g., face recognition, tracking of moving cars and people etc. it is very difficult to visualize complex structures in three-dimensional image volumes without cutting away large portions of, perhaps important, data. Tools, such as segmentation, can aid the medical staff in browsing through such large images by highlighting objects of particular importance. In addition, segmentation in particular can output models of organs, tumors, and other structures for further analysis, quantification or simulation. A different imaging tests, such as Ultrasound, CT or MRI scans, or X-rays. Ultrasound images/videos are Analysis are crucial, because it is non-invasive and is usually painless. It is widely available, easy-to-use and less expensive than other imaging methods. Ultrasound, also called sonography, uses sound waves to develop ultrasound images of what's going on inside the body. Ultrasound image analysis is used in order to quantify the status of a diseased stroke individually and take possible action by identifying the exact problem and the area of interest, extract information and propose some possible treatment. The segmentation techniques like balloon, active contour, Hough transform, Bayesian model, deformable model may be used to detect atherosclerotic carotid plaque for analysis.

Keywords: Segmentation; Ultrasound Medical Imaging; Active Contour; Hough Transform; Carotid Plaque

References

1. https://www.studyblue.com/notes/note/n/zeb-anatomy orapharneck/deck/3631984
2. https://content.onlinejacc.org/article.aspx?articleid=1138221
3. Loizou Christos P., et al. “Segmentation of atherosclerotic carotid plaque in ultrasound video”. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2012): 53-56.
4. Abirami MS and Dr T Sheela. "Analysis of image segmentation techniques for medical images”. In Proceedings of International Conference on Emerging Research in Computing, Information, Communication and Applications (2014).
5. Petroudi, Styliani., et al. “Segmentation of the common carotid intima-media complex in ultrasound images using active contours”. IEEE Transactions on Biomedical Engineering11 (2012): 3060-3069.
6. Xu Xiangyang., et al. “Ultrasound intima-media segmentation using Hough transform and dual snake model”. Computerized Medical Imaging and Graphics 3 (2012): 248-258.
7. Kass Michael., et al. “Snakes: Active contour models”. International Journal of Computer Vision4 (1988): 321-331.
8. Naik Vaishali., et al. “Carotid artery segmentation in ultrasound images and measurement of intima-media thickness”. BioMed Research International 2013 (2013).
9. https://www2.phy.ilstu.edu/~wenning/slh/Absolute%20Relative%20Error.pdf.
10. Data base of Ultrasound images.
11. https://www.glencoe.com/sites/pdfs/impact_math/ls9_c1_mean_absolute_d eviation.pdf
12. https://cgm.cs.mcgill.ca/~godfried/teaching/cgprojects/98/normand/main.html#algorithm
13. https://developers.google.com/maps/documentation/utilities/polylineutility?hl=en.
14. https://www.fimmonline.com/pub/en/data/objects/reproduciblity_validity.pdf
15. Dhupia Abhijeet., et al. “Automatic segmentation of lumen intima layer in longitudinal mode ultrasound images”. In 2020 42^nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2020): 2125-2128.
16. Loizou Christos P., et al. “An integrated system for the segmentation of atherosclerotic carotid plaque ultrasound video”. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 1 (2014): 86-101.
17. Destrempes François., et al. “Segmentation of plaques in sequences of ultrasonic B-mode images of carotid arteries based on motion estimation and a Bayesian model”. IEEE Transactions on Biomedical Engineering8 (2011): 2202-2211.
18. Loizou Christos P. "A review of ultrasound common carotid artery image and video segmentation techniques”. Medical and Biological Engineering and Computing 12 (2014): 1073-1093.

Citation

Citation: Ketki C Pathak and Sejal Patel. “Segmentation Method for Medical Ultrasound Signal Analysis”.Acta Scientific Orthopaedics 5.12 (2022): 103-115.

Copyright

Copyright: © 2022 Ketki C Pathak and Sejal Patel. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.