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Optimized Tree Strategy with Principal Component Analysis Using Feature Selection-Based Classification for Newborn

Debabrata Samanta1, M P Karthikeyan2, Marimuthu Karuppiah3

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This study introduces an automated method for grading newborn jaundice using principal component analysis (PCA) and an optimal tree classifier on histopathology images. This approach enhances diagnostic accuracy and efficiency for neonatal hyperbilirubinemia detection.

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Area of Science:

  • Medical Imaging
  • Computational Pathology
  • Neonatology

Background:

  • Newborn jaundice grading is a critical yet challenging area in medical research.
  • Accurate mitotic count is essential for determining jaundice severity in newborns.
  • Traditional methods for jaundice detection can be time-consuming and less precise.

Purpose of the Study:

  • To develop an automated system for mitotic detection and jaundice grading in newborns using histopathology images.
  • To improve the accuracy and efficiency of neonatal hyperbilirubinemia assessment.
  • To investigate the impact of feature selection on classification performance.

Main Methods:

  • Utilized principal component analysis (PCA) for feature selection.
  • Employed an optimal tree strategy classifier for automatic mitotic detection.
  • Applied image processing techniques to analyze real-time and benchmark histopathology datasets.

Main Results:

  • The developed system demonstrated accurate, quick, and time-efficient results for newborn jaundice detection.
  • Image processing techniques were found to be critical for predicting neonatal hyperbilirubinemia.
  • The combination of feature selection and classification models addressed performance bottlenecks.

Conclusions:

  • Automated mitotic detection and grading using PCA and optimal tree classifiers offer a promising approach for neonatal jaundice assessment.
  • Image processing is vital for accurate prediction and diagnosis of neonatal hyperbilirubinemia.
  • The proposed method provides a reliable and efficient alternative to conventional jaundice grading techniques.