Cardiac segmentation with strong anatomical guarantees
Convolutional neural networks (CNN) have had unprecedented success in medical imaging
and, in particular, in medical image segmentation. However, despite the fact that …
and, in particular, in medical image segmentation. However, despite the fact that …
Generating synthetic labeled data from existing anatomical models: an example with echocardiography segmentation
Deep learning can bring time savings and increased reproducibility to medical image
analysis. However, acquiring training data is challenging due to the time-intensive nature of …
analysis. However, acquiring training data is challenging due to the time-intensive nature of …
Early detection of myocardial infarction in low-quality echocardiography
Myocardial infarction (MI), or commonly known as heart attack, is a life-threatening health
problem worldwide from which 32.4 million people suffer each year. Early diagnosis and …
problem worldwide from which 32.4 million people suffer each year. Early diagnosis and …
Assisted probe guidance in cardiac ultrasound: A review
Echocardiography is the most frequently used imaging modality in cardiology. However, its
acquisition is affected by inter-observer variability and largely dependent on the operator's …
acquisition is affected by inter-observer variability and largely dependent on the operator's …
Learning with context feedback loop for robust medical image segmentation
KB Girum, G Crehange… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Deep learning has successfully been leveraged for medical image segmentation. It employs
convolutional neural networks (CNN) to learn distinctive image features from a defined pixel …
convolutional neural networks (CNN) to learn distinctive image features from a defined pixel …
MV-RAN: Multiview recurrent aggregation network for echocardiographic sequences segmentation and full cardiac cycle analysis
Multiview based learning has generally returned dividends in performance because
additional information can be extracted for the representation of the diversity of different …
additional information can be extracted for the representation of the diversity of different …
Improved segmentation of echocardiography with orientation-congruency of optical flow and motion-enhanced segmentation
Quantification of left ventricular (LV) ejection fraction (EF) from echocardiography depends
upon the identification of endocardium boundaries as well as the calculation of end-diastolic …
upon the identification of endocardium boundaries as well as the calculation of end-diastolic …
Multilevel structure-preserved GAN for domain adaptation in intravascular ultrasound analysis
The poor generalizability of intravascular ultrasound (IVUS) analysis methods caused by the
great diversity of IVUS datasets is hopefully addressed by the domain adaptation strategy …
great diversity of IVUS datasets is hopefully addressed by the domain adaptation strategy …
Interactive translation in echocardiography training system with enhanced cycle-GAN
L Teng, Z Fu, Y Yao - IEEE access, 2020 - ieeexplore.ieee.org
Interactive translation in echocardiography training system refers to the pixel-wise
translation between ultrasound cardiac and theoretical sketch images in the course of hand …
translation between ultrasound cardiac and theoretical sketch images in the course of hand …
Cardiac point-of-care to cart-based ultrasound translation using constrained CycleGAN
Purpose The emerging market of cardiac handheld ultrasound (US) is on the rise. Despite
the advantages in ease of access and the lower cost, a gap in image quality can still be …
the advantages in ease of access and the lower cost, a gap in image quality can still be …