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An Efficient Automated Detection of Schizophrenia Using k-NN and Bag of Words Features

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Abstract

Converging shreds of evidence from several research argue that the aberrations present in a brain’s Structural Magnetic Resonance Imaging (sMRI) are the leading cause of Schizophrenia, a severe psychiatric disorder. The augmentation of the application of Machine Learning (ML) in detecting mental diseases has led to an automated and accurate diagnosis. The automated diagnosis of Schizophrenia using ML has been implemented in this paper. The objective of this study is to create a Computer Aided Diagnosis (CAD) system to classify schizophrenia and normal control. The proposed framework used Scale-Invariant Feature Transform (SIFT), a local feature descriptor, to extract distinctive features from the pre-processed sMRI images. Mini Batch k-means clustering has been applied to cluster the feature vectors (descriptors) obtained from the SIFT detector. Then, the Bag of Words (BoW) approach was used to create histograms of the clusters created after clustering. The histograms of the individual visual words have been used as the training data for the k-Nearest Neighbor (k-NN) algorithm. The k-NN classifier with BoW features demonstrated promising results using SIFT feature extraction technique and provided significantly encouraging performance for schizophrenia detection.

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Data availability

The dataset used in the study is the Center for Biomedical Research Excellence (COBRE) dataset which is publicly available. It has been acquired from The Mind Research Network for Neurodiagnostic Discovery. Online—http://fcon_1000.projects.nitrc.org/indi/retro/cobre.html.

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  1. CSED, MNNIT Allahabad, Prayagraj, India

    Ashima Tyagi, Vibhav Prakash Singh & Manoj Madhava Gore

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  1. Ashima Tyagi
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This article is part of the topical collection “Research Trends in Computational Intelligence” guest edited by Anshul Verma, Pradeepika Verma, Vivek Kumar Singh and S. Karthikeyan.

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Tyagi, A., Singh, V.P. & Gore, M.M. An Efficient Automated Detection of Schizophrenia Using k-NN and Bag of Words Features. SN COMPUT. SCI. 4, 518 (2023). https://doi.org/10.1007/s42979-023-01947-2

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