AIMC Topic: Ultrasonography

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C-Net: Cascaded convolutional neural network with global guidance and refinement residuals for breast ultrasound images segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Breast lesions segmentation is an important step of computer-aided diagnosis system. However, speckle noise, heterogeneous structure, and similar intensity distributions bring challenges for breast lesion segmentation.

Automatic detection of A-line in lung ultrasound images using deep learning and image processing.

Medical physics
BACKGROUND: Auxiliary diagnosis and monitoring of lung diseases based on lung ultrasound (LUS) images is important clinical research. A-line is one of the most common indicators of LUS that can offer support for the assessment of lung diseases. A tra...

Deep learning-based diagnosis from endobronchial ultrasonography images of pulmonary lesions.

Scientific reports
Endobronchial ultrasonography with a guide sheath (EBUS-GS) improves the accuracy of bronchoscopy. The possibility of differentiating benign from malignant lesions based on EBUS findings may be useful in making the correct diagnosis. The convolutiona...

Deep Learning Estimation of Median Nerve Volume Using Ultrasound Imaging in a Human Cadaver Model.

Ultrasound in medicine & biology
Median nerve swelling is one of the features of carpal tunnel syndrome (CTS), and ultrasound measurement of maximum median nerve cross-sectional area is commonly used to diagnose CTS. We hypothesized that volume might be a more sensitive measure than...

Particle Swarm Optimized Fuzzy CNN With Quantitative Feature Fusion for Ultrasound Image Quality Identification.

IEEE journal of translational engineering in health and medicine
Inherently ultrasound images are susceptible to noise which leads to several image quality issues. Hence, rating of an image's quality is crucial since diagnosing diseases requires accurate and high-quality ultrasound images. This research presents a...

Ultrasound Evaluation of Pelvic Floor Function after Transumbilical Laparoscopic Single-Site Total Hysterectomy Using Deep Learning Algorithm.

Computational and mathematical methods in medicine
This study was aimed at investigating the ultrasound based on deep learning algorithm to evaluate the rehabilitation effect of transumbilical laparoscopic single-site total hysterectomy on pelvic floor function in patients. The bilinear convolutional...

Accurate assessment of the lung sliding artefact on lung ultrasonography using a deep learning approach.

Computers in biology and medicine
Pneumothorax is a potentially life-threatening condition that can be rapidly and accurately assessed via the lung sliding artefact generated using lung ultrasound (LUS). Access to LUS is challenged by user dependence and shortage of training. Image c...

DeepACSA: Automatic Segmentation of Cross-Sectional Area in Ultrasound Images of Lower Limb Muscles Using Deep Learning.

Medicine and science in sports and exercise
PURPOSE: Muscle anatomical cross-sectional area (ACSA) can be assessed using ultrasound and images are usually evaluated manually. Here, we present DeepACSA, a deep learning approach to automatically segment ACSA in panoramic ultrasound images of the...

Establishment of a deep-learning system to diagnose BI-RADS4a or higher using breast ultrasound for clinical application.

Cancer science
Although the categorization of ultrasound using the Breast Imaging Reporting and Data System (BI-RADS) has become widespread worldwide, the problem of inter-observer variability remains. To maintain uniformity in diagnostic accuracy, we have develope...