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GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation

IEEE International Conference on Computer Vision, 2023
Echocardiogram video segmentation plays an important role in cardiac disease diagnosis. This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentation, where the goal is to generalize the model trained on the source ...
Jiewen Yang   +4 more
semanticscholar   +1 more source

Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2023
Image synthesis is expected to provide value for the translation of machine learning methods into clinical practice. Fundamental problems like model robustness, domain transfer, causal modelling, and operator training become approachable through ...
Hadrien Reynaud   +7 more
semanticscholar   +1 more source

Deep Learning Pipeline for Echocardiogram Noise Reduction

2022 IEEE 7th International conference for Convergence in Technology (I2CT), 2022
The echocardiogram is an imaging modality based on ultrasound imaging of the heart and neighboring regions for assessing heart functions. It is employed to understand how the heart chambers and valves pump the blood and can be used to detect heart ...
G. Sanjeevi   +3 more
semanticscholar   +1 more source

CardiacNet: Learning to Reconstruct Abnormalities for Cardiac Disease Assessment from Echocardiogram Videos

European Conference on Computer Vision
Echocardiogram video plays a crucial role in analysing cardiac function and diagnosing cardiac diseases. Current deep neural network methods primarily aim to enhance diagnosis accuracy by incorporating prior knowledge, such as segmenting cardiac ...
Jiewen Yang   +5 more
semanticscholar   +1 more source

Local large language models for privacy-preserving accelerated review of historic echocardiogram reports

J. Am. Medical Informatics Assoc.
OBJECTIVES The study developed framework that leverages an open-source Large Language Model (LLM) to enable clinicians to ask plain-language questions about a patient's entire echocardiogram report history.
A. Vaid   +10 more
semanticscholar   +1 more source

Training-Free Condition Video Diffusion Models for single frame Spatial-Semantic Echocardiogram Synthesis

International Conference on Medical Image Computing and Computer-Assisted Intervention
Conditional video diffusion models (CDM) have shown promising results for video synthesis, potentially enabling the generation of realistic echocardiograms to address the problem of data scarcity.
Nguyen Van Phi   +3 more
semanticscholar   +1 more source

Fetal Congenital Heart Disease Echocardiogram Screening Based on DGACNN: Adversarial One-Class Classification Combined with Video Transfer Learning

IEEE Transactions on Medical Imaging, 2020
Fetal congenital heart disease (FHD) is a common and serious congenital malformation in children. In Asia, FHD birth defect rates have reached as high as 9.3%.
Yuxin Gong   +7 more
semanticscholar   +1 more source

Echocardiogram in sternal fracture

The American Journal of Emergency Medicine, 2001
We reviewed the records of 50 consecutive patients presenting with sternal fracture after blunt chest trauma. The relationships between electrocardiogram, creatine kinase MB isoenzyme and echocardiogram (ECHO) were assessed in reference to myocardial contusion.
Y, Wiener   +3 more
openaire   +2 more sources

Unnecessary Pre-Operative Cardiology Evaluation and Transthoracic Echocardiogram Delays Time to Surgery for Geriatric Hip Fractures.

Journal of Orthopaedics and Trauma, 2020
OBJECTIVE Delays to surgery for geriatric hip fracture patients are associated with increased morbidity and mortality. The American Heart Association (AHA) and American College of Cardiology (ACC) Clinical practice guidelines (CPG) were created to ...
Christopher L. Hoehmann   +6 more
semanticscholar   +1 more source

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