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Title

Enhanced CNN Model for Brain Tumor Classification

Author

Aravinda Kasukurthi, Lakshmikanth Paleti, Madamanchi Brahmaiah , Ch.Sudha Sree

Citation

Vol. 22  No. 5  pp. 143-148

Abstract

Brain tumor is one of the serious cancers around the world. It occurs due to the separation of brain cells. It is widespread cancer in adults and children. Premature identification of the disease is essential for dropping the death rate due to risks of brain tumor cancer. Several computer-aided diagnosis (CAD) systems proposed recently in detection of cancer diseases to assist radiologists.Recently several deep learning techniques explored in detection of brain tumour. In this paper, we proposed a new model “Enhanced Convolution Neural Network (ECNN)” for indentifying brain tumour which leading to improve disease detection. During the performance evaluation, different experiments conducted on existed brain tumor datasets using existing CNN models and with proposed ECN. The results entrenched the superiority of ECN when compared to other CNN models.

Keywords

Convolution Neural Network, Tumor Classification, computer-aided diagnosis (CAD) systems

URL

http://paper.ijcsns.org/07_book/202205/20220521.pdf