Fine grained automatic left ventricle segmentation via ROI based Tri-Convolutional neural networks.

Journal: Technology and health care : official journal of the European Society for Engineering and Medicine
PMID: 39058464

Abstract

BACKGROUND: The left ventricle segmentation (LVS) is crucial to the assessment of cardiac function. Globally, cardiovascular disease accounts for the majority of deaths, posing a significant health threat. In recent years, LVS has gained important attention due to its ability to measure vital parameters such as myocardial mass, end-diastolic volume, and ejection fraction. Medical professionals realize that manually segmenting data to evaluate these processes takes a lot of time, effort when diagnosing heart diseases. Yet, manually segmenting these images is labour-intensive and may reduce diagnostic accuracy.

Authors

  • Gayathri K
    Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India.
  • Uma Maheswari N
    Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India.
  • Venkatesh R
    Department of Information Technology, PSNA College of Engineering and Technology, Dindigul, Tamil Nadu, India.
  • Ganesh Prabu B
    Department of Electrical and Electronics Engineering, University College of Engineering Dindigul, Tamil Nadu, India.

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