Feb 1, 2020

Comparison of morphometric parameters in prediction of hydrocephalus using random forests

Computers in Biology and Medicine
Busra Ozgode YiginGorkem Saygili

Abstract

Ventricles of the human brain enlarge with aging, neurodegenerative diseases, intrinsic, and extrinsic pathologies. The morphometric examination of neuroimages is an effective approach to assess structural changes occurring due to diseases such as hydrocephalus. In this study, we explored the effectiveness of commonly used morphological parameters in hydrocephalus diagnosis. For this purpose, the effect of six common morphometric parameters; Frontal Horns' Length (FHL), Maximum Lateral Length (MLL), Biparietal Diameter (BPD), Evans' Ratio (ER), Cella Media Ratio (CMR), and Frontal Horns' Ratio (FHR) were compared in terms of their importance in predicting hydrocephalus using a Random Forest classifier. The experimental results demonstrated that hydrocephalus can be detected with 91.46 % accuracy using all of these measurements. The accuracy of classification using only CMR and FHL reached up to 93.33 %. In terms of individual performances, CMR and FHL were the top performers whereas BPD and FHR did not contribute as much to the overall accuracy.

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Mentioned in this Paper

Classification
Morphological
Birth Length
Structure
Transvaginal Ultrasound: Fetal Biparietal Diameter
Internal
Detected (Finding)
Pathology
Hydrocephalus
Morphometric Analysis

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