Cortical Bone Thickness Assessment from Multi-frequency Ultrasound RF Data using a Convolutional Architecture with Multi-head Attention

Enrico Grisan, Sevan Harput, Hossam H. Sultan, P. Dryburgh, L. Peralta

Research output: Contribution to conferencePaperpeer-review

2 Citations (Scopus)
2 Downloads (Pure)

Abstract

Cortical bone thickness is an important predictor of bone strength and fracture risk, and accurate classification is crucial for the diagnosis and treatment of osteoporosis. The thinning of the cortical layer, indicative of compromised bone microarchitecture due to imbalanced formation and loss, underscores its significance. Nonetheless, quantifying bone thickness is challenging due to the diverse skeletal sites and subject variations in bone structure and properties.A potential solution lies in multi-frequency ultrasound assessment of cortical bone, enabling comprehensive property characterization across varying wavelengths and penetration depths. This research strives to establish a robust methodology for evaluating cortical bone thickness by leveraging a convolutional model with an attention mechanism to analyse multi-frequency ultrasound data.
Original languageEnglish
DOIs
Publication statusPublished - 3 Sept 2023
Event2023 IEEE International Ultrasonics Symposium (IUS) -
Duration: 9 Mar 2023 → …

Conference

Conference2023 IEEE International Ultrasonics Symposium (IUS)
Period9/03/23 → …

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