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Diagnosis of Fetal Brain Abnormalities Using Ex Learning

  • 2026
  • OriginalPaper
  • Chapter
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Abstract

This chapter delves into the innovative use of deep learning and convolutional neural networks (CNNs) to diagnose fetal brain abnormalities from ultrasound scans. It covers the methodology of acquiring and preprocessing MRI images, extracting relevant features, and training CNNs to classify images as normal or pathological. The results highlight the model's high accuracy and the potential for early detection of abnormalities. The chapter also discusses the implications of these findings for prenatal care and the future of AI-driven diagnostics in healthcare. Additionally, it compares the effectiveness of deep learning with traditional methods and explores the challenges and opportunities in implementing these technologies in clinical settings.

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Title
Diagnosis of Fetal Brain Abnormalities Using Ex Learning
Authors
Ch. Sravanthi
K. Kavya Sri
V. Varshitha
V. Keerthi
Copyright Year
2026
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-95-0269-1_12
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