AI Medical Compendium Topic:
Ultrasonography

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DGANet: A Dual Global Attention Neural Network for Breast Lesion Detection in Ultrasound Images.

Ultrasound in medicine & biology
Deep learning-based breast lesion detection in ultrasound images has demonstrated great potential to provide objective suggestions for radiologists and improve their accuracy in diagnosing breast diseases. However, the lack of an effective feature en...

Good view frames from ultrasonography (USG) video containing ONS diameter using state-of-the-art deep learning architectures.

Medical & biological engineering & computing
This paper presents an automated method for detection of the diagnostically prominent frames containing optic nerve sheath (ONS) from ocular ultrasonography video using deep learning; such frames are referred to as "Good View" frames in this paper. V...

How much can AI see in early pregnancy: A multi-center study of fetus head characterization in week 10-14 in ultrasound using deep learning.

Computer methods and programs in biomedicine
PURPOSE: To investigate if artificial intelligence can identify fetus intracranial structures in pregnancy week 11-14; to provide an automated method of standard and non-standard sagittal view classification in obstetric ultrasound examination METHOD...

Analysis of facial ultrasonography images based on deep learning.

Scientific reports
Transfer learning using a pre-trained model with the ImageNet database is frequently used when obtaining large datasets in the medical imaging field is challenging. We tried to estimate the value of deep learning for facial US images by assessing the...

Minimizing Image Quality Loss After Channel Count Reduction for Plane Wave Ultrasound via Deep Learning Inference.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
High-frame-rate ultrasound imaging uses unfocused transmissions to insonify an entire imaging view for each transmit event, thereby enabling frame rates over 1000 frames per second (fps). At these high frame rates, it is naturally challenging to real...

A deep learning approach to median nerve evaluation in ultrasound images of carpal tunnel inlet.

Medical & biological engineering & computing
Ultrasound (US) imaging is recognized as a useful support for Carpal Tunnel Syndrome (CTS) assessment through the evaluation of median nerve morphology. However, US is still far to be systematically adopted to evaluate this common entrapment neuropat...

Automatic Segmentation of Periodontal Tissue Ultrasound Images with Artificial Intelligence: A Novel Method for Improving Dataset Quality.

Sensors (Basel, Switzerland)
UNLABELLED: This research aimed to evaluate Mask R-CNN and U-Net convolutional neural network models for pixel-level classification in order to perform the automatic segmentation of bi-dimensional images of US dental arches, identifying anatomical el...

Domain generalization for prostate segmentation in transrectal ultrasound images: A multi-center study.

Medical image analysis
Prostate biopsy and image-guided treatment procedures are often performed under the guidance of ultrasound fused with magnetic resonance images (MRI). Accurate image fusion relies on accurate segmentation of the prostate on ultrasound images. Yet, th...

Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization.

Computers in biology and medicine
OBJECTIVE: Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These tech...

Artificial intelligence for identification of focal lesions in intraoperative liver ultrasonography.

Langenbeck's archives of surgery
PURPOSE: Intraoperative ultrasonography (IOUS) of the liver is a crucial adjunct in every liver resection and may significantly impact intraoperative surgical decisions. However, IOUS is highly operator dependent and has a steep learning curve. We de...