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A Survey on Optimization Methods Used for Early Prediction and Diagnosis of Schizophrenia Disorder

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Metaheuristics and Optimization in Computer and Electrical Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1077))

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Abstract

MRI is the most influential and flexible tool used for the diagnosis of various pathological alterations of living tissues. Identification of structural abnormalities in brain has become a rising attention for the early prediction and diagnosis of schizophrenia from the healthy controls. Recognizing the biomarkers in schizophrenic patients and related conditions will be highly beneficial in discriminating the psychic disorder. Neuro imaging explains the brain images by using the information provided by either of these techniques like computed tomography, magnetic resonance imaging and positron emission tomography, out of which Structural neuroimaging studies can provide some of the most consistent evidence for brain abnormalities in schizophrenia. The motivation of the work is to get more significant diagnostic data. As the electronically captured images might be inappropriate and needed to be fine-tuned such as removing the noise, separating different shades using segmentation operations and many more. To analyze the magnetic resonance imaging methodologies used in non-invasive clinical investigations more affectively, these can be upgraded by the application of suitable optimization methods. In many studies it is evident that the conventional mathematical models are not enough in obtaining better solutions for real-time applications. Coming to medical imaging accuracy is playing much more important role in early diagnosis and treatment suggestions. To obtain the best solution medical imaging and diagnosis optimization techniques are playing a much more important role nowadays. Especially nature-inspired algorithms. Here a detailed survey has been made to show how the optimization techniques can be used effectively in obtaining accurate data to characterize disease-related alterations in brain structures and used for early diagnosis.

S. Prabha--Freelance Researcher.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Hindustan Institute of Technology and Science, Chennai, Tamil Nadu, 603103, India

    N. Swathi

  2. Jacksonville, FL, USA

    S. Prabha

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  1. N. Swathi
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  2. S. Prabha
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Correspondence to S. Prabha .

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Editors and Affiliations

  1. Department of Industrial Engineering, Ankara Yıldırım Beyazıt University (AYBU), Ankara, Türkiye

    Navid Razmjooy

  2. Department of Industrial Engineering, Ankara Yıldırım Beyazıt University (AYBU), Ankara, Türkiye

    Noradin Ghadimi

  3. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, India

    Venkatesan Ra**ikanth

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Swathi, N., Prabha, S. (2023). A Survey on Optimization Methods Used for Early Prediction and Diagnosis of Schizophrenia Disorder. In: Razmjooy, N., Ghadimi, N., Ra**ikanth, V. (eds) Metaheuristics and Optimization in Computer and Electrical Engineering. Lecture Notes in Electrical Engineering, vol 1077. Springer, Cham. https://doi.org/10.1007/978-3-031-42685-8_15

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