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                                       Details for article 11 of 11 found articles
 
 
  Statistical classification of magnetic resonance images of brain employing random forest classifier
 
 
Title: Statistical classification of magnetic resonance images of brain employing random forest classifier
Author: Joshi S.
Deepa Shenoy P.
Venugopal K. R.
Patnaik L.M.
Appeared in: International journal of machine intelligence
Paging: Volume 1 (2009) nr. 2 pages 55-61
Year: 2009
Contents: Data mining in brain imaging is an emerging field of high importance for providing prognosis,treatment, and a deeper understanding of how the brain functions. Dementia due to Alzheimer’s diseaseconstitutes the fourth most common disorder among the elderly. Early detection of dementia and correctstaging of the severity of dementia is critical to select the optional treatment. The present study wasdesigned to classify and categorize brain images of dementia patients into three distinct classes i.e., Normal,Moderately diseased, and Severe. Decision Forest Classifier was employed to classify the various MagneticResonance Images (MRIs) of dementia patients. Results of screening the MRIs are organized byclassification and finally grouped into the three categories, i.e., Normal, Moderate and Severe. Experimentalresults obtained indicated that the proposed method performs relatively well with the classification accuracyreaching nearly 99.32% in comparison with the already existing algorithms.
Publisher: Bioinfo Publications (provided by DOAJ)
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 11 of 11 found articles
 
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