AI Medical Compendium Topic:
Ultrasonography

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Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.

European radiology
OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk.

Remote Expert DVT Triaging of Novice-User Compression Sonography with AI-Guidance.

Annals of vascular surgery
BACKGROUND: Compression ultrasonography of the leg is established for triaging proximal lower extremity deep vein thrombosis (DVT). AutoDVT, a machine-learning software, provides a tool for nonspecialists in acquiring compression sequences to be revi...

Development and validation of an artificial intelligence assisted prenatal ultrasonography screening system for trainees.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: Fetal anomaly screening via ultrasonography, which involves capturing and interpreting standard views, is highly challenging for inexperienced operators. We aimed to develop and validate a prenatal-screening artificial intelligence system ...

Rib region detection for scanning path planning for fully automated robotic abdominal ultrasonography.

International journal of computer assisted radiology and surgery
PURPOSE: Scanning path planning is an essential technology for fully automated ultrasound (US) robotics. During biliary scanning, the subcostal boundary is critical body surface landmarks for scanning path planning but are often invisible, depending ...

Deep learning for fast denoising filtering in ultrasound localization microscopy.

Physics in medicine and biology
Addition of a denoising filter step in ultrasound localization microscopy (ULM) has been shown to effectively reduce the error localizations of microbubbles (MBs) and achieve resolution improvement for super-resolution ultrasound (SR-US) imaging. How...

Immune response and mesenchymal transition of papillary thyroid carcinoma reflected in ultrasonography features assessed by radiologists and deep learning.

Journal of advanced research
INTRODUCTION: Ultrasonography (US) features of papillary thyroid cancers (PTCs) are used to select nodules for biopsy due to their association with tumor behavior. However, the molecular biological mechanisms that lead to the characteristic US featur...

Approaches and Limitations of Machine Learning for Synthetic Ultrasound Generation: A Scoping Review.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
This scoping review examines the emerging field of synthetic ultrasound generation using machine learning (ML) models in radiology. Nineteen studies were analyzed, revealing three primary methodological strategies: unconditional generation, condition...

A despeckling method for ultrasound images utilizing content-aware prior and attention-driven techniques.

Computers in biology and medicine
The despeckling of ultrasound images contributes to the enhancement of image quality and facilitates precise treatment of conditions such as tumor cancers. However, the use of existing methods for eliminating speckle noise can cause the loss of image...

Ultra-fast ultrasound blood flow velocimetry for carotid artery with deep learning.

Artificial intelligence in medicine
Accurate measurement of blood flow velocity is important for the prevention and early diagnosis of atherosclerosis. However, due to the uncertainty of parameter settings, the autocorrelation velocimetry methods based on clutter filtering are prone to...

Predicting carcass tissue composition in Blackbelly sheep using ultrasound measurements and machine learning methods.

Tropical animal health and production
This study aimed to predict Blackbelly sheep carcass tissue composition using ultrasound measurements and machine learning models. The models evaluated were decision trees, random forests, support vector machines, and multi-layer perceptrons and were...