AIMC Topic: Echocardiography

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Deep Learning-Based Computer-Aided Fetal Echocardiography: Application to Heart Standard View Segmentation for Congenital Heart Defects Detection.

Sensors (Basel, Switzerland)
Accurate segmentation of fetal heart in echocardiography images is essential for detecting the structural abnormalities such as congenital heart defects (CHDs). Due to the wide variations attributed to different factors, such as maternal obesity, abd...

A machine learning framework for the evaluation of myocardial rotation in patients with noncompaction cardiomyopathy.

PloS one
AIMS: Noncompaction cardiomyopathy (NCC) is considered a genetic cardiomyopathy with unknown pathophysiological mechanisms. We propose to evaluate echocardiographic predictors for rigid body rotation (RBR) in NCC using a machine learning (ML) based m...

Making Artificial Intelligence Lemonade Out of Data Lemons: Adaptation of a Public Apical Echo Database for Creation of a Subxiphoid Visual Estimation Automatic Ejection Fraction Machine Learning Algorithm.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: A paucity of point-of-care ultrasound (POCUS) databases limits machine learning (ML). Assess feasibility of training ML algorithms to visually estimate left ventricular ejection fraction (EF) from a subxiphoid (SX) window using only apica...

Prospects for cardiovascular medicine using artificial intelligence.

Journal of cardiology
As the importance of artificial intelligence (AI) in the clinical setting increases, the need for clinicians to understand AI is also increasing. This review focuses on the fundamental principles of AI and the current state of cardiovascular AI. Vari...

Deep learning evaluation of biomarkers from echocardiogram videos.

EBioMedicine
BACKGROUND: Laboratory testing is routinely used to assay blood biomarkers to provide information on physiologic state beyond what clinicians can evaluate from interpreting medical imaging. We hypothesized that deep learning interpretation of echocar...

Generating Synthetic Labeled Data From Existing Anatomical Models: An Example With Echocardiography Segmentation.

IEEE transactions on medical imaging
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 labeling and high inter-observer variability in annotations. Rather than...

A category attention instance segmentation network for four cardiac chambers segmentation in fetal echocardiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Fetal echocardiography is an essential and comprehensive examination technique for the detection of fetal heart anomalies. Accurate cardiac chambers segmentation can assist cardiologists to analyze cardiac morphology and facilitate heart disease diag...

Artificial intelligence applied to support medical decisions for the automatic analysis of echocardiogram images: A systematic review.

Artificial intelligence in medicine
The echocardiogram is a test that is widely used in Heart Disease Diagnoses. However, its analysis is largely dependent on the physician's experience. In this regard, artificial intelligence has become an essential technology to assist physicians. Th...

Deep Learning Brings New Era in Echocardiography.

Circulation journal : official journal of the Japanese Circulation Society