ArticleScientific reports2022
Quantitative imaging of ultrasound backscattered signals with information entropy for bone microstructure characterization.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 13 citations in OpenAlex.
- High-frequency quantitative ultrasound in characterizing human skin aging: an exploration of the non-modeling and modeling approaches.Quantitative imaging in medicine and surgery · 2025Article
- Changes in mechanical properties at the muscle level could be detected by Nakagami imaging during in-vivo fixed-end contractions.PloS one · 2024Article
- Ultrasound Characterization of Cortical Bone Using Shannon Entropy.Ultrasound in medicine & biology · 2023Article
- Transmastoid Ultrasound Detection of Middle Ear Effusion and Its Association with Clinical Audiometric Tests.Life (Basel, Switzerland) · 2022Article
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Authors and funding
7 authors at 4 institutions in 1 country.
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Abstract
Osteoporosis is a critical problem during aging. Ultrasound signals backscattered from bone contain information associated with microstructures. This study proposed using entropy imaging to collect the information in bone microstructures as a possible solution for ultrasound bone tissue characterization. Bone phantoms with different pounds per cubic foot (PCF) were used for ultrasound scanning by using single-element transducers of 1 (nonfocused) and 3.5 MHz (nonfocused and focused). Clinical measurements were also performed on lumbar vertebrae (L3 spinal segment) in participants with different ages (n = 34) and postmenopausal women with low or moderate-to-high risk of osteoporosis (n = 50; identified using the Osteoporosis Self-Assessment Tool for Taiwan). The signals backscattered from the bone phantoms and subjects were acquired for ultrasound entropy imaging by using sliding window processing. The independent t-test, one-way analysis of variance, Spearman correlation coefficient r
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