High intensity focused ultrasound (HIFU) is a thriving non-invasive technique for thermal ablation of tumors, but significant challenges remain in its real-time monitoring with medical imaging. Ultrasound imaging is one of the main imaging modalities for monitoring HIFU surgery in organs other than the brain, mainly due to its good temporal resolution. However, strong acoustic interference from HIFU irradiation severely obscures the B-mode images and compromises the monitoring. To address this problem, we proposed a frequency-domain robust principal component analysis (FRPCA) method to separate the HIFU interference from the contaminated B-mode images. Ex-vivo and in-vivo experiments were conducted to validate the proposed method based on a clinical HIFU therapy system combined with an ultrasound imaging platform. The performance of the FRPCA method was compared with the conventional notch filtering method. Results demonstrated that the FRPCA method can effectively remove HIFU interference from the B-mode images, which allowed HIFU-induced grayscale changes at the focal region to be recovered. Compared to notch-filtered images, the FRPCA-processed images showed an 8.9% improvement in terms of the structural similarity (SSIM) index to the uncontaminated B-mode images. These findings demonstrate that the FRPCA method presents an effective signal processing framework to remove the strong HIFU acoustic interference, obtains better dynamic visualization in monitoring the HIFU irradiation process, and offers great potential to improve the efficacy and safety of HIFU treatment and other focused ultrasound related applications.
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http://dx.doi.org/10.1109/TMI.2024.3385408 | DOI Listing |
Background And Objective: To assess whether conventional brightness-mode (B-mode) transrectal ultrasound images of the prostate reveal clinically significant cancers with the help of artificial intelligence methods.
Methods: This study included 2986 men who underwent biopsies at two institutions. We trained the PROstate Cancer detection on B-mode transrectal UltraSound images NETwork (ProCUSNet) to determine whether ultrasound can reliably detect cancer.
J Cachexia Sarcopenia Muscle
February 2025
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
Background: Diaphragm thickness is a potential marker of sarcopenia in addition to muscle mass and strength at extremities. We aimed to clarify the descriptive epidemiology and prognostic significance of diaphragm thickness in the general population.
Methods: The study participants were 3324 community residents (mean age: 61.
Ultrasound Med Biol
January 2025
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology - NTNU, Trondheim, Norway; Health Research, SINTEF, Trondheim, Norway.
Objective: To develop and compare methods to automatically estimate regional ultrasound image quality for echocardiography separate from view correctness.
Methods: Three methods for estimating image quality were developed: (i) classic pixel-based metric: the generalized contrast-to-noise ratio (gCNR), computed on myocardial segments (region of interest) and left ventricle lumen (background), extracted by a U-Net segmentation model; (ii) local image coherence: the average local coherence as predicted by a U-Net model that predicts image coherence from B-mode ultrasound images at the pixel level; (iii) deep convolutional network: an end-to-end deep-learning model that predicts the quality of each region in the image directly. These methods were evaluated against manual regional quality annotations provided by three experienced cardiologists.
J Clin Med
January 2025
Department of Internal Medicine, Angiology, and Physical Medicine, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, Batorego 15 St., 41-902 Bytom, Poland.
The interrelationship of thyroid volume and function with features of cardiovascular dysfunction has already been investigated but some aspects remain unclear, especially in terms of subclinical cardiovascular dysfunction in euthyroid patients. Intima-media thickness (IMT) measurement in ultrasound B-mode imaging in different vascular beds (most frequently within the common carotid artery) is one of the most important tools for the detection of subclinical atherosclerosis in both clinical practice and research. This article aimed to present the results of our research on the association between the thyroid evaluation parameters and the IMT measured in both the carotid and femoral arteries in euthyroid patients aged 18 to 65 years taking into account the influence of diabetes, hypertension, and excess body mass.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Department of Neurosurgery, Río Hortega University Hospital, 47014 Valladolid, Spain.
Intraoperative ultrasound (ioUS) provides real-time imaging during neurosurgical procedures, with advantages such as portability and cost-effectiveness. Accurate tumor segmentation has the potential to substantially enhance the interpretability of ioUS images; however, its implementation is limited by persistent challenges, including noise, artifacts, and anatomical variability. This study aims to develop a convolutional neural network (CNN) model for glioma segmentation in ioUS images via a multicenter dataset.
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