Internet of things mathematical approach for detecting brain tumor

  • Authors

    • Noor Kareem Jumaa Al-Mansour University College
    • Auday A.H Mohamad Al-Mansour University College
    • Sameer Hameed Majeed Al-Mansour University College
    2018-10-06
    https://doi.org/10.14419/ijet.v7i4.16283
  • Internet of Things, Health care, Brain tumor, MRI, SVM.

  • Brain is highly important organ which makes us able to walk, breath, and all other activities; without brain lives can’t do all of that. The importance of brain functions made it critical to make any not precisely measured medical action. Currently; computer vision is very important in medical field, where it helps specialists to precisely diagnose and take the right decision before making surgeries. This article worked on accommodating the technology of internet of things (IoT) for serving brain medicine specialist in the field of identifying the need of making surgeries depending on magnetic resonance imaging (MRI) images. Support Vector Machine (SVM) algorithm is used to detect brain tumor and segment it from MRI morphological images. Putting SVM on IoT Thingspeak platform will help brain specialist to diagnose MRI images that are received from MRI computerized system online. The obtained results are compared with same algorithm implemented locally with assist of Matlab program version R2017a.

     

     

  • References

    1. [1] Neha Rani and Sharda Vashisth,â€Brain Tumor Detection and Classification with Feed Forward Back-Prop Neural Networkâ€, International journal of computer applications, Vol. 146, No.12, (2016).

      [2] Tanvi Gupta, Pranay Manocha, Tapan K. Gandhi, R.K. Gupta, and B.K. Panigrahia (2002), Tumor classification and segmentation of MRI brain images, Fortis memorial research institute, Gurgaon, India.

      [3] Miss. Priyanka Katti and Mr. V. R. Marathe, â€Implementation of Classification System for Brain Tumor using Probabilistic Neural Networkâ€, International journal of advanced research in computer and communication engineering, Vol. 4, Issue. 10, (2015).

      [4] Dipali B.Birnale and S. N. Patil,â€Brain Tumor MRI Image Segmentation using FCM and SVM Techniquesâ€, International journal of engineering science and computing, Vol. 6, No. 12, (2016).

      [5] Jia Li, Dhiraj Joshi, and James Z. Wang, Stochastic modeling of volume images with a 3-D hidden markov model, US National Science Foundation, USA.

      [6] Sajjad Hussain Talpur,â€The Appliance Pervasive of Internet of Things in Healthcare Systemsâ€, International journal of computer science issues, Vol. 10, Issue. 1, No. 1, (2013).

      [7] Hyo-Sik Ham, Hwan-Hee Kim, Myung-Sup Kim, and Mi-Jung Choi, â€Linear SVM-Based Android Malware Detection for Reliable IoT Servicesâ€, Journal of applied mathematics, Vol., (2014).

      [8] Internet Society (2015), the internet of things: an overview, available online: www.internetsociety.org.

      [9] Nandhini.K and B.Sanithi,â€Retrospection of SVM classifierâ€, Journal of theoretical and applied information technology, Vol. 38, No. 1, (2012).

      [10] Swapnil R. Telrandhe, Amit Pimpalkar, and Ankita Kendhe, â€Implementation of Brain Tumor Detection using Segmentation Algorithm & SVMâ€, International journal on computer science and engineering, Vol. 8, No.7, (2016).

      [11] Ms. Shinde Sayali P. and Ms. Phalle Vaibhavi N,â€A Survey Paper on Internet of Things based Healthcare Systemâ€, International advanced research journal in science, engineering and technology, Vol. 4, Special Issue 4, (2017).

      [12] Richa Aggarwal and Amanpreet Kaur,â€Efficient Analysis of Brain Tumor Detection and Identification Using Different Algorithmsâ€, International journal of sciences & research technology, Vol. 3, (2014).

      [13] www.thingspeak.com.

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  • How to Cite

    Kareem Jumaa, N., A.H Mohamad, A., & Hameed Majeed, S. (2018). Internet of things mathematical approach for detecting brain tumor. International Journal of Engineering & Technology, 7(4), 2779-2783. https://doi.org/10.14419/ijet.v7i4.16283