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      Comparison of morphometric parameters in prediction of hydrocephalus using random forests

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      Author
      Özgöde-Yigin, B.
      Algın, Oktay
      Saygılı, G.
      Date
      2020-01-01
      Source Title
      Computers in Biology and Medicine
      Print ISSN
      0010-4825
      Publisher
      Elsevier
      Volume
      116
      Language
      English
      Type
      Article
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      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.
      Keywords
      Hydrocephalus
      Morphological parameters
      Feature importance
      Semi-automatic analysis
      Permalink
      http://hdl.handle.net/11693/75524
      Published Version (Please cite this version)
      https://doi.org/10.1016/j.compbiomed.2019.103547
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      • National Magnetic Resonance Research Center (UMRAM) 197
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