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Analysis of schizophrenia using support vector machine classifier

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Abstract

Schizophrenia affects the substances of the brain, which decreases the volume of the brain and leads to mental disorder. This work deals with the study of using computer aided technique on early diagnose of schizophrenia. Statistical parametric mapping (SPM) is used to separate Gray matter, White matter, and Cerebrospinal fluid from Brain and computed the volume of the brain. We also executed 2D SURF and FAST features and identified the apt feature vector for diagnosing Schizophrenia accurately. Principal Component Analysis is used to find out the most promising feature vectors and SVM Classifier is used to diagnose whether the user was affected by Schizophrenia or not. During the analysis, it was found that FAST feature overperforms the SURF feature in early diagnose of Schizophrenia and results were compared with earlier work.

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Data available on request from the authors.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Dr. Sivanthi Aditanar College of Engineering, Thoothukudi, Tiruchendur, India

    G. Wiselin Jiji

  2. Scientist, Vikram Sarabhai Space Centre, Indian Space Research Organization, Veli, Thiruvananthapuram, Kerala, 695022, India

    A. Rajesh

  3. Department of Computer Science & Engineering, Dr. Sivanthi Aditanar College of Engineering, Thoothukudi, Tiruchendur, India

    Ajitha Kanagaraj

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  1. G. Wiselin Jiji
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Correspondence to G. Wiselin Jiji.

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Jiji, G.W., Rajesh, A. & Kanagaraj, A. Analysis of schizophrenia using support vector machine classifier. Multimed Tools Appl 82, 32505–32517 (2023). https://doi.org/10.1007/s11042-023-14513-y

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  • DOI: https://doi.org/10.1007/s11042-023-14513-y

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