Automatic ROI detection and classification of the Achilles tendon ultrasound images

Conference paper

Benrabha, JS and Meziane, F. 2017. Automatic ROI detection and classification of the Achilles tendon ultrasound images. 1st International Conference on Internet of Things and Machine Learning. New York, USA 17 - 18 Oct 2017 ACM Press. https://doi.org/10.1145/3109761.3158381
AuthorsBenrabha, JS and Meziane, F.
TypeConference paper
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%.

KeywordsAchilles tendon; ; Image classification; ; Medical image processing; ; Region of Interest
Year2017
Conference1st International Conference on Internet of Things and Machine Learning
JournalACM International Conference Proceeding Series
PublisherACM Press
Digital Object Identifier (DOI)https://doi.org/10.1145/3109761.3158381
Web address (URL)https://doi.org/10.1145/3109761.3158381
ISBN978-145035243-7
Web address (URL) of conference proceedingshttps://dl.acm.org/doi/proceedings/10.1145/3109761
Publication dates18 Oct 2017
Publication process dates
Deposited05 Jun 2023
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Alshehri, H. and Meziane, F. 2014. The Effect of recommendations from family members and friends and third party endorsement in B2C E-Commerce: The case of Saudi Arabia. 24th International Business Information Management Association Conference - Crafting Global Competitive Economies: 2020 Vision Strategic Planning and Smart Implementation. Milan, Italy 06 - 07 Nov 2014 IBIMA.