In the field of high-frequency ultrasound imaging ( MHz), tools for characterizing the performance of imaging systems are lacking. Indeed, commercial phantoms are often inadequate for this frequency range. The development of homemade phantoms on the laboratory scale is often required but is hindered by the difficulty in making very small structures that must be distributed with high accuracy in 3-D space. We propose investigating the use of 3-D photopolymer printing to create resolution and calibration phantoms designed for high-frequency ultrasound imaging. The quality and importance of these phantoms are discussed from the point of view of ultrasound parameters and imaging. First, the compressional wave group velocity, acoustic impedance, and attenuation of six photopolymerized materials were measured using temporal and spectral methods in a substitution experimental setup. Measurements were performed on printed samples using a broadband-focused single-element transducer covering a large frequency range (15-55 MHz). Two 3-D phantoms incorporating different shapes and dimensions were designed and printed. Finally, 3-D acoustic images were obtained using either a mechanically driven single-element transducer or a high-frequency commercial imaging system. Three-dimensional printing enabled us to generate phantoms suitable for high-frequency imaging with complex geometry inclusions and with a surrounding material having acoustic properties close to those of human skin. The calculated SNR between the inclusion and surrounding media is approximately 50 dB. In conclusion, 3-D printing is a useful tool for directly, easily, and rapidly manufacturing ultrasound phantoms for ultrasound imaging system assessments and computational calibration or validation.
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http://dx.doi.org/10.1109/TUFFC.2018.2823545 | DOI Listing |
Nanomedicine (Lond)
January 2025
Department of Ultrasound, Yantaishan Hospital, Binzhou Medical University, Yantai, Shandong, China.
With the rapid development of nanotechnology, nanoultrasonography has emerged as a promising medical imaging technique that demonstrates significant potential in the diagnosis and treatment of gastrointestinal (GI) diseases. This review discusses the applications of nanoultrasonography in the gastrointestinal field, including improvements in imaging resolution, diagnostic accuracy, latest research findings, and prospects for clinical application. By analyzing existing literature, we explore the role of nanoultrasonography in enhancing imaging resolution, enabling targeted drug delivery, and improving therapeutic outcomes, thereby providing a reference for future research directions.
View Article and Find Full Text PDFJ Int Med Res
January 2025
Department of Gynecology, The Third People's Hospital of Yunnan Province, Guandu District, Kunming, China.
We report the case of a woman in her early 30 s who was diagnosed with Robert's uterus. She had been experiencing progressive dysmenorrhea for a decade and sought treatment for infertility at our hospital. Preoperative ultrasound imaging resulted in a misdiagnosis of a complete uterine septum with an accompanying ovarian cyst.
View Article and Find Full Text PDFFront Vet Sci
January 2025
Department of Veterinary Medicine and Animal Production, University of Naples, Federico II, Naples, Italy.
Introduction: Ultrasound imaging (US) is the method of choice to assess the canine prostate gland. Whilst recent studies have documented the role of castration in the development of prostatic neoplasia, little is known about parenchymal and perfusion features of the normal and abnormal prostate in neutered dogs. No data are available concerning prostatic changes after the first 90 days following castration.
View Article and Find Full Text PDFTrauma Surg Acute Care Open
January 2025
Trauma and Acute Care Surgery, Inova Health System, Falls Church, Virginia, USA.
Eur J Obstet Gynecol Reprod Biol X
March 2025
Mother and Newborn Health Research Center, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
This review examines the emerging applications of machine learning (ML) and radiomics in the diagnosis and prediction of placenta accreta spectrum (PAS) disorders, addressing a significant challenge in obstetric care. It highlights recent advancements in ML algorithms and radiomic techniques that utilize medical imaging modalities like magnetic resonance imaging (MRI) and ultrasound for effective classification and risk stratification of PAS. The review discusses the efficacy of various deep learning models, such as nnU-Net and DenseNet-PAS, which have demonstrated superior performance over traditional diagnostic methods through high AUC scores.
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