Automatic ROI detection and classification of the Achilles tendon ultrasound images

Benrabha, JS; Meziane, F

Abstract

Ultrasound (US) imaging plays an important role in medical
imaging technologies. It is widely used because of its ease of use
and low cost compared to other imaging techniques. Specifically,
ultrasound imaging is used in the detection of the Achilles Tendon
(AT) pathologies as it detects important details. For example, US
imaging is used for AT rupture that affects about 1 in 5,000
people worldwide. Decision support systems are important in
medical imaging, as they assist radiologist in detecting probable
diagnoses and lesions. The work presented in this paper concerns
the development of a software application to detect changes in the
AT ultrasound images and subsequently classify them into normal
or abnormal. We propose an approach that fully automates the
detection for the Region of Interest (ROI) in ultrasound AT
images. The original image is divided into six blocks with 1 cm
size in each direction. The blocks lie inside the vulnerable area
considered as our ROI. The proposed system achieved an
accuracy of 97.21%.

Citation

Benrabha, J., & Meziane, F. (2017, October). Automatic ROI detection and classification of the Achilles tendon ultrasound images. Presented at International Conference on Internet of Things and Machine Learning (IML2017), Liverpool, United Kingdom

• Presentation Conference Type: Other
• Conference Name: International Conference on Internet of Things and Machine Learning (IML2017)
• Conference Location: Liverpool, United Kingdom
• Start Date: Oct 17, 2017
• End Date: Oct 18, 2017
• Acceptance Date: Jul 12, 2017
• Publication Date: Oct 18, 2017
• Deposit Date: Sep 13, 2017
• Publicly Available Date: May 30, 2018
• DOI: https://doi.org/10.1145/3109761.3158381
• Publisher URL: https://doi.org/10.1145/3109761.3158381
• Related Public URLs: http://dl.acm.org/; https://iml-conference.org/
• Additional Information: Additional Information : Proceedings ISBN: 978-1-4503-5243-7; Event Type : Conference