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AuthorAl-Mohannadi A.
AuthorAl-Maadeed, Somaya
AuthorElharrouss O.
AuthorSadasivuni K.K.
Available date2022-05-19T10:23:06Z
Publication Date2021
Publication NameSensors
ResourceScopus
Identifierhttp://dx.doi.org/10.3390/s21206839
URIhttp://hdl.handle.net/10576/31084
AbstractCardiovascular diseases (CVDs) have shown a huge impact on the number of deaths in the world. Thus, common carotid artery (CCA) segmentation and intima-media thickness (IMT) measurements have been significantly implemented to perform early diagnosis of CVDs by analyzing IMT features. Using computer vision algorithms on CCA images is not widely used for this type of diagnosis, due to the complexity and the lack of dataset to do it. The advancement of deep learning techniques has made accurate early diagnosis from images possible. In this paper, a deep-learning-based approach is proposed to apply semantic segmentation for intima-media complex (IMC) and to calculate the cIMT measurement. In order to overcome the lack of large-scale datasets, an encoder-decoder-based model is proposed using multi-image inputs that can help achieve good learning for the model using different features. The obtained results were evaluated using different image segmentation metrics which demonstrate the effectiveness of the proposed architecture. In addition, IMT thickness is computed, and the experiment showed that the proposed model is robust and fully automated compared to the state-of-the-art work.
SponsorFunding: This publication was supported by Qatar University Internal Grant No. IRCC-2020-013 and Sultan Qaboos University through Grant # CL/SQU-QU/ENG/20/01, respectively. The findings achieved herein are solely the responsibility of the authors.
Languageen
PublisherMDPI
SubjectDecoding
Deep learning
Image segmentation
Large dataset
Semantic Segmentation
Semantics
Signal encoding
Ultrasonics
Cardiovascular disease
Carotid intima-media thickness
Common carotid artery
Deep learning
Early diagnosis
Encoder-decoder
Encoder-decoder architecture
Encoder-decoder model
Intima-media thickness
Segmentation
Diagnosis
algorithm
arterial wall thickness
common carotid artery
diagnostic imaging
early diagnosis
echography
Algorithms
Carotid Artery, Common
Carotid Intima-Media Thickness
Early Diagnosis
Ultrasonography
TitleEncoder-decoder architecture for ultrasound IMC segmentation and cIMT measurement
TypeArticle
Issue Number20
Volume Number21
dc.accessType Abstract Only


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