Normalized Spatial Autocorrelation in Ultrasound B-Mode Imaging for Point-Scatterer Detection.

Delay multiply and sum Normalized spatial autocorrelation Point-scatterer detection Sidelobes Speckle reduction Ultrasound B-mode imaging

Journal

Ultrasound in medicine & biology
ISSN: 1879-291X
Titre abrégé: Ultrasound Med Biol
Pays: England
ID NLM: 0410553

Informations de publication

Date de publication:
May 2024
Historique:
received: 24 06 2023
revised: 03 01 2024
accepted: 06 01 2024
medline: 18 3 2024
pubmed: 9 2 2024
entrez: 8 2 2024
Statut: ppublish

Résumé

Point-scatterer detection plays a key role in medical ultrasound B-mode imaging. Speckle noise and insufficient spatial resolution are important factors affecting point-scatterer detection. To address this issue, normalized spatial autocorrelation in ultrasound B-mode imaging (NSACB) is proposed. First, the acquired data are pre-processed by adding Gaussian white noise (GWN) with a certain signal-to-Gaussian white noise ratio (SGWNR). Next, normalized spatial autocorrelation is applied to the pre-processed data, and the data are divided into several new signals with different spatial lags. Then, the new signals are performed unsigned delay multiply and sum. Finally, the NSACB beamformed data are bandpass filtered by extracting the frequency component around twice the center frequency. Simulated and in vitro experiments were designed for validation. Simulations revealed that the lateral resolution of NSACB measured by the -6-dB mainlobe width can reach as high as 11.11% of delay and sum (DAS), 25.01% of filtered delay multiply and sum (F-DMAS) and 50% of LAG-FDMAS-SCF. The sidelobe level of the NSACB can be reduced at most by 28 dB. Experimental results of simple and complex scatterer phantoms indicate the image resolution of the proposed NSACB can even reach up to 18.76% of DAS, 27.28% of F-DMAS and 14.29% of LAG-FDMAS-SCF. Compared with these methods, the proposed NSACB can reduce the sidelobe level at least by 18 dB. Although the proposed method causes loss of the ability to observe hypo-echoic structures, these results suggest future work to determine the ability to detect breast microcalcifications, kidney stones, biopsy needle tracking and other scenarios requiring scatterer detection.

Identifiants

pubmed: 38331698
pii: S0301-5629(24)00009-7
doi: 10.1016/j.ultrasmedbio.2024.01.009
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

690-702

Informations de copyright

Copyright © 2024 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest The authors declare no competing interests.

Auteurs

Cuijuan Lou (C)

Key Laboratory of Grain Information Processing and Control, Henan University of Technology, Ministry of Education, Zhengzhou, China; Henan Key Laboratory of Grain Photoelectric Detection and Control, Henan University of Technology, Zhengzhou, China; School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou, China. Electronic address: loucuijuan2006@126.com.

Zhaohui Liu (Z)

Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.

Ming Yuchi (M)

Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.

Mingyue Ding (M)

Department of Biomedical Engineering, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.

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Classifications MeSH