Abstract
Image segmentation is dividing of medical imaging into parts and extracting the regions of interest. The study involves the images of brain tumors where the tumor part is segmented from the image and analyzed accurately and efficiently. Convolution Neural Network (CNN) has made a tremendous progress in the field of the Medical and Information Technology. With CNN model, one may not be able to reorganize higher risk patients to get immediate aid they require but also communicate through the network to the clinicians, surgeons, eventually improving the standard of patient care in the medical system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yin Z et al (2015) A clinical decision support system for the diagnosis of probable migraine and probable tension-type headache based on case-based reasoning. J Headache Pain 16:29
Moses AJ et al (2006) Computer-aided diagnoses of chronic head pain: explanation, study data, implications, and challenges. J Craniomandibular Pract
Grill E et al (2016) Developing and implementing diagnostic prediction models for vestibular diseases in primary care. In: Exploring complexity in health: an interdisciplinary systems approach
Mirarchi D et al (2016) Applying mining techniques to analyze vestibular data. Elsevier Procedia Comput Sci 98(2016):467–472
Nishara Banu MA, Gomathy B (2013) Disease predicting system using data mining techniques. Int J Tech Res Appl. e-ISSN: 2320-8163
Halicek M et al (2017) Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging. J Biomed Opt 22(6):060503
Prisilla J et al (2017) Deep learning in oncology—a case study on brain tumor. Int J Cancer Res Ther. ISSN: 2476-237
Prisilla J (2016) The butterfly network in medical care using clouds services. ICTBIG IEEE. https://doi.org/10.1109/ictbig.2016.7892655. Electronic ISBN: 978-1-5090-5515-9
Chen K, Seuret M (2017) Convolutional neural networks for page segmentation of historical document images
Gonzalez RC, Woods RE, Digital image processing. Pearson Education Asia
Conflicts of Interest
Prisilla Jayanthi is the principal investigator of the CNN study and involved in script making. Dr. I. V. Murali Krishna is a keen guide in directing the research work and giving the novel ideas. The X-ray reports were collected from the Gandhi Hospital, Secunderabad, India and thanks for their support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Prisilla, J., Iyyanki, V.M.K. (2019). Convolution Neural Networks: A Case Study on Brain Tumor Segmentation in Medical Care. In: Pandian, D., Fernando, X., Baig, Z., Shi, F. (eds) Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB). ISMAC 2018. Lecture Notes in Computational Vision and Biomechanics, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-030-00665-5_98
Download citation
DOI: https://doi.org/10.1007/978-3-030-00665-5_98
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00664-8
Online ISBN: 978-3-030-00665-5
eBook Packages: EngineeringEngineering (R0)