Koninklijke Bibliotheek, National Library of the NetherlandsIP1343504211802.1
45479df41fa9bfae04356afbef3501dd
Bioinfo Publications
International Journal of Machine Intelligence
09752927
09759166
2009-12-30
1
2
55
61
Statistical classification of magnetic resonance images of brain employing random forest classifier
Joshi S.
Deepa Shenoy P.
Venugopal K. R.
Patnaik L.M.
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.
http://www.bioinfo.in/uploadfiles/12615752481_2_11_IJMI.pdf
Data mining
Machine learning
Dementia
Alzheimer’s disease
Random forest classifier
]]>
45479df41fa9bfae04356afbef3501dd
Bioinfo Publications
International Journal of Machine Intelligence
09752927
09759166
2009-12-30
1
2
55
61
Statistical classification of magnetic resonance images of brain employing random forest classifier
Joshi S.
Deepa Shenoy P.
Venugopal K. R.
Patnaik L.M.
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.
http://www.bioinfo.in/uploadfiles/12615752481_2_11_IJMI.pdf
Data mining
Machine learning
Dementia
Alzheimer’s disease
Random forest classifier
09752927-20110712-082344.zip45479df41fa9bfae04356afbef3501dd.pdfPDF1.3
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