AIMC Topic: Ultrasonography

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Perceiving placental ultrasound image texture evolution during pregnancy with normal and adverse outcome through machine learning prism.

Placenta
INTRODUCTION: The objective was to perform placental ultrasound image texture (UPIA) in first (T1), second(T2) and third(T3) trimesters of pregnancy using machine learning( ML).

Unsupervised deep learning-based displacement estimation for vascular elasticity imaging applications.

Physics in medicine and biology
. Arterial wall stiffness can provide valuable information on the proper function of the cardiovascular system. Ultrasound elasticity imaging techniques have shown great promise as a low-cost and non-invasive tool to enable localized maps of arterial...

Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers.

EBioMedicine
BACKGROUND: For patients with early-stage breast cancers, neoadjuvant treatment is recommended for non-luminal tumors instead of luminal tumors. Preoperative distinguish between luminal and non-luminal cancers at early stages will facilitate treatmen...

Robotic ultrasound imaging: State-of-the-art and future perspectives.

Medical image analysis
Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Rob...

Deep-learning based segmentation of ultrasound adipose image for liposuction.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: To develop an automatic and reliable ultrasonic visual system for robot- or computer-assisted liposuction, we examined the use of deep learning for the segmentation of adipose ultrasound images in clinical and educational settings.

Clinical Applications, Challenges, and Recommendations for Artificial Intelligence in Musculoskeletal and Soft-Tissue Ultrasound: Expert Panel Narrative Review.

AJR. American journal of roentgenology
Artificial intelligence (AI) is increasingly used in clinical practice for musculoskeletal imaging tasks, such as disease diagnosis and image reconstruction. AI applications in musculoskeletal imaging have focused primarily on radiography, CT, and MR...

Use of artificial intelligence and deep learning in fetal ultrasound imaging.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Deep learning is considered the leading artificial intelligence tool in image analysis in general. Deep-learning algorithms excel at image recognition, which makes them valuable in medical imaging. Obstetric ultrasound has become the gold standard im...

Automated fundus ultrasound image classification based on siamese convolutional neural networks with multi-attention.

BMC medical imaging
Fundus ultrasound image classification is a critical issue in the medical field. Vitreous opacity (VO) and posterior vitreous detachment (PVD) are two common eye diseases, Now, the diagnosis of these two diseases mainly relies on manual identificatio...

Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit.

Critical care (London, England)
BACKGROUND: Interpreting point-of-care lung ultrasound (LUS) images from intensive care unit (ICU) patients can be challenging, especially in low- and middle- income countries (LMICs) where there is limited training available. Despite recent advances...

Ultrasound Localization Microscopy Using Deep Neural Network.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Noninvasive imaging of microvascular structures in deep tissues provides morphological and functional information for clinical diagnosis and monitoring. Ultrasound localization microscopy (ULM) is an emerging imaging technique that can generate micro...