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Found 8 papers, 4 papers with code
Automatic retrieval of corresponding US views in longitudinal examinations
Skeletal muscle atrophy is a common occurrence in critically ill patients in the intensive care unit (ICU) who spend long periods in bed.
Towards Realistic Ultrasound Fetal Brain Imaging Synthesis
The results of this work illustrate the potential of GAN-based methods to synthesise realistic high-resolution ultrasound images, leading to future work with other fetal brain planes, anatomies, devices and the need of a pool of experts to evaluate synthesised images.
A Machine Learning Case Study for AI-empowered echocardiography of Intensive Care Unit Patients in low- and middle-income countries
We present a Machine Learning (ML) study case to illustrate the challenges of clinical translation for a real-time AI-empowered echocardiography system with data of ICU patients in LMICs.
Empirical Study of Quality Image Assessment for Synthesis of Fetal Head Ultrasound Imaging with DCGANs
In this work, we present an empirical study of DCGANs, including hyperparameter heuristics and image quality assessment, as a way to address the scarcity of datasets to investigate fetal head ultrasound.
B-line Detection in Lung Ultrasound Videos: Cartesian vs Polar Representation
As a result, we hypothesize that a polar representation may be more adequate for automatic image analysis of these images.
Automatic Detection of B-lines in Lung Ultrasound Videos From Severe Dengue Patients
Lung ultrasound (LUS) imaging is used to assess lung abnormalities, including the presence of B-line artefacts due to fluid leakage into the lungs caused by a variety of diseases.
Scene and Environment Monitoring Using Aerial Imagery and Deep Learning
In this paper, a review of studies applying deep learning on UAV imagery for smart farming is presented.
Semi-supervised GAN for Classification of Multispectral Imagery Acquired by UAVs
The results by the proposed semi-supervised GAN achieves high classification accuracy and demonstrates the potential of GAN-based methods for the challenging task of multispectral image classification.
