AIMC Topic: Ultrasonography

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A Human-Centered Machine-Learning Approach for Muscle-Tendon Junction Tracking in Ultrasound Images.

IEEE transactions on bio-medical engineering
Biomechanical and clinical gait research observes muscles and tendons in limbs to study their functions and behaviour. Therefore, movements of distinct anatomical landmarks, such as muscle-tendon junctions, are frequently measured. We propose a relia...

An image classification deep-learning algorithm for shrapnel detection from ultrasound images.

Scientific reports
Ultrasound imaging is essential for non-invasively diagnosing injuries where advanced diagnostics may not be possible. However, image interpretation remains a challenge as proper expertise may not be available. In response, artificial intelligence al...

PFP-LHCINCA: Pyramidal Fixed-Size Patch-Based Feature Extraction and Chi-Square Iterative Neighborhood Component Analysis for Automated Fetal Sex Classification on Ultrasound Images.

Contrast media & molecular imaging
OBJECTIVES: Fetal sex determination with ultrasound (US) examination is indicated in pregnancies at risk of X-linked genetic disorders or ambiguous genitalia. However, misdiagnoses often arise due to operator inexperience and technical difficulties w...

The feasibility to use artificial intelligence to aid detecting focal liver lesions in real-time ultrasound: a preliminary study based on videos.

Scientific reports
Despite the wide availability of ultrasound machines for hepatocellular carcinoma surveillance, an inadequate number of expert radiologists performing ultrasounds in remote areas remains a primary barrier for surveillance. We demonstrated feasibility...

A machine learning approach applied to gynecological ultrasound to predict progression-free survival in ovarian cancer patients.

Archives of gynecology and obstetrics
In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promising tool for implementing complex multi-parametric decision-making algorithms. Regarding ovarian cancer (OC), despite the standardization of features t...

Deep learning-based plane pose regression in obstetric ultrasound.

International journal of computer assisted radiology and surgery
PURPOSE: In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimensional (2D) US image represents a major challenge in skill acquisition. We aim to build a US plane local...

Investigating Shift Variance of Convolutional Neural Networks in Ultrasound Image Segmentation.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
While accuracy is an evident criterion for ultrasound image segmentation, output consistency across different tests is equally crucial for tracking changes in regions of interest in applications such as monitoring the patients' response to treatment,...

Neural Network Kalman Filtering for 3-D Object Tracking From Linear Array Ultrasound Data.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Many interventional surgical procedures rely on medical imaging to visualize and track instruments. Such imaging methods not only need to be real time capable but also provide accurate and robust positional information. In ultrasound (US) application...

Deep Learning-Based Classification of Reduced Lung Ultrasound Data From COVID-19 Patients.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The application of lung ultrasound (LUS) imaging for the diagnosis of lung diseases has recently captured significant interest within the research community. With the ongoing COVID-19 pandemic, many efforts have been made to evaluate LUS data. A four...

Deep-Learning Based Adaptive Ultrasound Imaging From Sub-Nyquist Channel Data.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Traditional beamforming of medical ultrasound images relies on sampling rates significantly higher than the actual Nyquist rate of the received signals. This results in large amounts of data to store and process, imposing hardware and software challe...