IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Ultrasound (US) has the unique potential to offer access to medical imaging to anyone, everywhere. Devices have become ultraportable and cost-effective, akin to the stethoscope. Nevertheless, and despite many advances, US image quality and diagnostic...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Ultrasound computed tomography (USCT) quantifies acoustic tissue properties such as the speed-of-sound (SOS). Although full-waveform inversion (FWI) is an effective method for accurate SOS reconstruction, it can be computationally challenging for lar...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Abdominal aortic aneurysms (AAAs) are rupture-prone dilatations of the aorta. In current clinical practice, the maximal diameter of AAAs is monitored with 2-D ultrasound to estimate their rupture risk. Recent studies have shown that 3-D and mechanica...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Autonomous ultrasound image quality assessment (US-IQA) is a promising tool to aid the interpretation by practicing sonographers and to enable the future robotization of ultrasound procedures. However, autonomous US-IQA has several challenges. Ultras...
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Freehand 3-D ultrasound imaging is emerging as a promising modality for regular spine exams due to its noninvasiveness and affordability. The laminae landmarks play a critical role in depicting the 3-D shape of the spine. However, the extraction of t...
OBJECTIVE: The ACR Thyroid Imaging, Reporting, and Data System (TI-RADS) uses a score based on ultrasound (US) imaging to stratify the risk of nodule malignancy and recommend appropriate follow-up. This study aims to analyze US reports and explore ho...
BACKGROUND: The integration of artificial intelligence (AI) and ultrasound (US) technology is reshaping facial aesthetics, providing enhanced diagnostic precision, procedural safety, and personalized patient care. The variability in US imaging, stemm...
MedSegBench is a comprehensive benchmark designed to evaluate deep learning models for medical image segmentation across a wide range of modalities. It covers a wide range of modalities, including 35 datasets with over 60,000 images from ultrasound, ...
OBJECTIVE: Deep learning approaches such as DeepACSA enable automated segmentation of muscle ultrasound cross-sectional area (CSA). Although they provide fast and accurate results, most are developed using data from healthy populations. The changes i...