Comparison of morphometric parameters in prediction of hydrocephalus using random forests
Author
Özgöde-Yigin, B.
Algın, Oktay
Saygılı, G.
Date
2020-01-01Source Title
Computers in Biology and Medicine
Print ISSN
0010-4825
Publisher
Elsevier
Volume
116
Language
English
Type
ArticleItem Usage Stats
5
views
views
2
downloads
downloads
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.