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August 15, 2025Acta medica LituanicaOpen Access

Automated Deep Learning Based Cardiac Quantification in Hypertrophic Cardiomyopathy: A Comparative Study with Manual Segmentation

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Authors

SAShivam AngirasDBDeb Kumar BoruahPPPranjal Phukan

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Overview

Comparative study shows deep learning automates cardiac quantification in hypertrophic cardiomyopathy, suggesting it may enhance workflow.

Key Points

  • Automated deep learning cardiac quantification closely matches manual measurements for key parameters across hypertrophic cardiomyopathy.
  • The study found high correlation coefficients: LVEF (r=0.91) and LVEDV (r=0.89), indicating reliable measurement by the automated approach.
  • Analysis utilized paired t-tests and Bland–Altman tests to evaluate the accuracy of the deep learning software against manual methods.
  • Integration of deep learning could streamline clinical workflows, highlighting the potential for improved efficiency.

Cite This Study

Angiras et al. (2025) studied this question.

synapsesocial.com/papers/68a34f6b234c60ad5c20c09chttps://doi.org/10.15388/amed.2025.32.2.8
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