This research applies machine learning methods to enhance the quality and clinical usefulness of echocardiographic images. By leveraging algorithms for noise reduction, segmentation, and structural feature enhancement, the system produces clearer and more accurate heart images for diagnostic evaluation. The study demonstrates how machine learning can help clinicians identify cardiac abnormalities more efficiently, improving diagnostic precision and patient outcomes. These advancements strengthen biomedical imaging workflows and support modern, AI-assisted cardiac healthcare practices.
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Multimedia Tools and Applications
https://link.springer.com/article/10.1007/s11042-022-13516-5