Submit your paper : editorIJETjournal@gmail.com

Paper Title : BRAIN TUMOUR DETECTION USING DEEP LEARNING

ISSN : 2395-1303
Year of Publication : 2022
10.5281/zenodo.7239104

Authors: Srivalli D, Sai Priya G, Jyothika M, Preethi M

         


Abstract
Nowaday’s tumor is second leading cause of cancer. The medical field needs automated, efficient and reliable technique to detect tumor like brain tumor. Detection plays very important role in treatment. If proper detection of tumor is possible then doctors keep a patient out of danger. Various image processing techniques are used in this application. Using this application doctors provide proper treatment and save a number of tumor patients. A tumor is nothing but excess cells growing in an uncontrolled manner. Currently, doctors locate the position and the area of brain tumor by looking at the MR Images of the brain of the patient manually. This results in inaccurate detection of the tumor and is considered very time consuming. A tumor is a mass of tissue it grows out of control. We can use a Deep Learning architectures CNN. The performance of model is predict image tumor is present or not in image. If the tumor is present it return yes otherwise return no.

Reference
[1] David N. Louis, Arie Perry, et al. , “The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary”, Acta Neuropathol , Springer may 2016 [2] Pär Salander, A Tommy Bergenheim, Katarina Hamberg, Roger Henriksson, Pathways from symptoms to medical care: a descriptive study of symptom development and obstacles to early diagnosis in brain tumour patients, Family Practice, Volume 16, Issue 2, April 1999, Pages 143–148, [3] McKinney PA ,”Brain tumours: incidence, survival, and aetiology”,Journal of Neurology, Neurosurgery & Psychiatry 2004;75:ii12-ii17. [4] Heimans, J., Taphoorn, M. Impact of brain tumour treatment on quality of life. J Neurol 249, 955–960 (2002) [5] Malavika Suresh, et al. “Real-Time Hand Gesture Recognition Using Deep Learning”, International Journal of Innovations and Implementations in Engineering(ISSN 2454- 3489), 2019, vol 1 [6] M. Gurbină, M. Lascu and D. Lascu, “Tumor Detection and Classification of MRI Brain Image using Different Wavelet Transforms and Support Vector Machines”, 42nd International Conference on Telecommunications and Signal Processing (TSP), Budapest, Hungary, 2019. [7] A. Sivaramakrishnan And Dr.M.Karnan “A Novel Based Approach For Extraction Of Brain Tumor In MRI Images Using Soft Computing Techniques,” International Journal Of Advanced Research In Computer And Communication Engineering, Vol. 2, Issue 4, April 2013.
Keywords
— Medical Image Processing, Brain tumour, MRI, Artificial neural network, CNN, Keras