International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
Mar. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 132
Paper Published : 1707
No. of Authors : 4723
  Journal Paper


Paper Title :
A Review on Brain Tumor Segmentation Techniques on MRI Images

Author :Mansi Singh, Kumari Kalyani, Tannu Yadav, Bhawna Yadav, Najme Zehra Naqvi

Article Citation :Mansi Singh ,Kumari Kalyani ,Tannu Yadav ,Bhawna Yadav ,Najme Zehra Naqvi , (2023 ) " A Review on Brain Tumor Segmentation Techniques on MRI Images " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 73-81, Volume-11,Issue-6

Abstract : Cancer has been increasingly affecting people of vast diversity in age, gender, origin, etc. This makes its timely diagnosis and treatment essential. A brain tumour is typically an abnormal development of brain cells that is either malignant (cancerous) or benign (non-cancerous). Brain tumors are very dangerous because it is quite hard to perform surgery on them owing to their sensitive location. Early detection of tumor and its classification into malignant or benign allows medical practition- ers to perform accurate diagnosis and hence, provide appropriate treatment. This paper introduces various contemporary state-of- the-art ML and DL methods used in brain tumor segmentation and their comparative study based on metrics of performance. Keywords - Medical Image Segmentation, Machine Learn- ing, Deep Learning, MRI

Type : Research paper

Published : Volume-11,Issue-6


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